Nothing
R/MIX.SUBMODEL.TVC_helper.R
In nlpsem: Linear and Nonlinear Longitudinal Process in Structural Equation Modeling Framework
Defines functions
getsub.TVC_l
Documented in
getsub.TVC_l
#' @title Define a Latent Growth Curve Model or Latent Change Score Model with a Time-varying Covariate as Class-specific Models
#' (Submodels) for a Longitudinal Mixture Model.
#'
#' @description This function defines a latent growth curve model or latent change score model with time-varying covariate as class-
#' specific models (submodels) for a longitudinal mixture model.
#'
#' @param dat A wide-format data frame, with each row corresponding to a unique ID. It contains the observed variables with
#' repeated measurements and occasions for each longitudinal process, and time-invariant covariates (TICs) if any.
#' It takes the value passed from \code{getMIX()}.
#' @param nClass An integer specifying the number of latent classes for the mixture model. It takes the value passed from \code{getMIX()}.
#' @param t_var A string specifying the prefix of the column names corresponding to the time variable at each study wave.
#' It takes the value passed from \code{getMIX()}.
#' @param y_var A string specifying the prefix of the column names corresponding to the outcome variable at each study wave.
#' It takes the value passed from \code{getMIX()}.
#' @param curveFun A string specifying the functional form of the growth curve. Supported options for \code{y_model =
#' "LGCM"} include: \code{"linear"} (or \code{"LIN"}), \code{"quadratic"} (or \code{"QUAD"}), \code{"negative exponential"}
#' (or \code{"EXP"}), \code{"Jenss-Bayley"} (or \code{"JB"}), and \code{"bilinear spline"} (or \code{"BLS"}). Supported
#' options for \code{y_model = "LCSM"} include: \code{"quadratic"} (or \code{"QUAD"}), \code{"negative exponential"}
#' (or \code{"EXP"}), \code{"Jenss-Bayley"} (or \code{"JB"}), and \code{"nonparametric"} (or \code{"NonP"}). It takes the
#' value passed from \code{getMIX()}.
#' @param intrinsic A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the
#' value passed from \code{getMIX()}.
#' @param records A numeric vector specifying the indices of the observed study waves. It takes the value passed from
#' \code{getMIX()}.
#' @param y_model A string specifying how to fit the longitudinal outcome. Supported values are \code{"LGCM"} and \code{"LCSM"}.
#' It takes the value passed from \code{getMIX()}.
#' @param TVC A string specifying the prefix of the column names corresponding to the time-varying covariate at each study wave.
#' It takes the value passed from \code{getMIX()}.
#' @param decompose An integer specifying the decomposition option for temporal states. Supported values include \code{0} (no
#' decomposition), \code{1} (decomposition with interval-specific slopes as temporal states), \code{2} (decomposition with interval-
#' specific changes as temporal states), and \code{3} (decomposition with change-from-baseline as temporal states). It takes the
#' value passed from \code{getMIX()}.
#' @param growth_TIC A string or character vector specifying the column name(s) of time-invariant covariate(s) that account for the
#' variability of growth factors, if any. It takes the value passed from \code{getMIX()}.
#' @param starts A list of initial values for the parameters, either takes the value passed from \code{getMIX()}
#' or derived by the helper function \code{getMIX.initial()}.
#'
#' @return A list of manifest and latent variables and paths for an mxModel object.
#'
#' @keywords internal
#'
#' @importFrom OpenMx mxPath mxModel mxAlgebraFromString mxMatrix mxFitFunctionML
#'
getsub.TVC_l <- function(dat, nClass, t_var, records, y_var, curveFun, intrinsic, y_model, TVC, decompose,
growth_TIC, starts){
## Define manifest variables
manifests <- c(paste0(TVC, records), paste0(y_var, records))
if (!is.null(growth_TIC)){
manifests <- c(manifests, growth_TIC)
}
# Define latent variables for the TVC for each type of decomposition
if (decompose != 0){
X_latents <- c("eta0x", "eta1x", paste0("lx", records), paste0("dx", records[-1]))
if (decompose == 2){
X_latents <- c(X_latents, paste0("deltax", records[-1]))
}
else if (decompose == 3){
X_latents <- c(X_latents, paste0("Deltax", records[-1]))
}
}
TVC_info <- getMIX_TVC.info(nClass = nClass, y_var = y_var, records = records, growth_TIC = growth_TIC, TVC = TVC,
decompose = decompose, starts = starts)
# Obtain factor loadigs for the specified functional form
GF_loadings <- getMIX_UNI.loadings(nClass = nClass, y_model = y_model, t_var = t_var, y_var = y_var,
curveFun = curveFun, intrinsic = intrinsic, records = records)
BETA <- class.list <- list()
## Define latent variables, growth factor loadings, paths of the longitudinal outcome
if (y_model == "LGCM"){
if (curveFun %in% c("linear", "LIN")){
latents <- c("eta0Y", "eta1Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("quadratic", "QUAD")){
latents <- c("eta0Y", "eta1Y", "eta2Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"), name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("negative exponential", "EXP")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "deltag")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (decompose == 1){
Y_nGF <- length(latents) - (length(records) * 2 - 1) - 2
}
else if (I(decompose == 2 | decompose == 3)) {
Y_nGF <- length(latents) - (length(records) * 2 - 1) - (length(records) - 1) - 2
}
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
}
else if (curveFun %in% c("Jenss-Bayley", "JB")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y", "deltag")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
}
else if (curveFun %in% c("bilinear spline", "BLS")){
if (intrinsic){
latents <- c("eta0sY", "eta1sY", "eta2sY", "deltag")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_mean_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_mean_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi0")),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC))"),
name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC)"),
name = paste0("c", k, "beta_s")),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0sY", "eta1sY", "eta2sY")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, 1] + c", k, "beta %*% c", k,
"mux"), name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_mean_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_mean_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi0")),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, 1] + c", k, "beta %*% c", k,
"BL_mean"), name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k, "beta2TVC)"),
name = paste0("c", k, "beta_s")),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 [1:3, 1]+ c", k, "beta %*% c", k,
"X_mueta0"), name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
}
}
else if (y_model == "LCSM"){
Y_PATH_L_L <- Y_PATH_SLP_L <- Y_PATH_AUTO_L <- list()
for (k in 1:nClass){
## Define paths from latent true scores to observed scores
Y_PATH_L <- mxPath(from = paste0("ly", records), to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1)
## Define paths from latent instantaneous rate of change at each measurement to true scores
Y_PATH_SLP <- mxPath(from = paste0("dy", records[-1]), to = paste0("ly", records[-1]), arrows = 1,
free = FALSE, values = 0, labels = paste0("lag", records[-1], "[1,1]"))
#### Define autoregressive paths
Y_PATH_AUTO <- mxPath(from = paste0("ly", records[-length(records)]), to = paste0("ly", records[-1]),
arrows = 1, free = FALSE, values = 1)
Y_PATH_L_L[[k]] <- Y_PATH_L
Y_PATH_SLP_L[[k]] <- Y_PATH_SLP
Y_PATH_AUTO_L[[k]] <- Y_PATH_AUTO
}
# Obtain additional parameters (derived) for the specified functional form
AddPara <- getMIX_UNI.addpara(dat = dat, nClass = nClass, curveFun = curveFun, intrinsic = intrinsic,
t_var = t_var, records = records, growth_TIC = growth_TIC, decompose = decompose,
starts = starts)
if (curveFun %in% c("nonparametric", "NonP")){
latents <- c("eta0Y", "eta1Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("quadratic", "QUAD")){
latents <- c("eta0Y", "eta1Y", "eta2Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("negative exponential", "EXP")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "deltag", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c",
k, "betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c",
k, "betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
}
else if (curveFun %in% c("Jenss-Bayley", "JB")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y", "deltag", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
}
}
return(class.list)
}
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Defines functions getsub.TVC_l
Documented in getsub.TVC_l
#' @title Define a Latent Growth Curve Model or Latent Change Score Model with a Time-varying Covariate as Class-specific Models
#' (Submodels) for a Longitudinal Mixture Model.
#'
#' @description This function defines a latent growth curve model or latent change score model with time-varying covariate as class-
#' specific models (submodels) for a longitudinal mixture model.
#'
#' @param dat A wide-format data frame, with each row corresponding to a unique ID. It contains the observed variables with
#' repeated measurements and occasions for each longitudinal process, and time-invariant covariates (TICs) if any.
#' It takes the value passed from \code{getMIX()}.
#' @param nClass An integer specifying the number of latent classes for the mixture model. It takes the value passed from \code{getMIX()}.
#' @param t_var A string specifying the prefix of the column names corresponding to the time variable at each study wave.
#' It takes the value passed from \code{getMIX()}.
#' @param y_var A string specifying the prefix of the column names corresponding to the outcome variable at each study wave.
#' It takes the value passed from \code{getMIX()}.
#' @param curveFun A string specifying the functional form of the growth curve. Supported options for \code{y_model =
#' "LGCM"} include: \code{"linear"} (or \code{"LIN"}), \code{"quadratic"} (or \code{"QUAD"}), \code{"negative exponential"}
#' (or \code{"EXP"}), \code{"Jenss-Bayley"} (or \code{"JB"}), and \code{"bilinear spline"} (or \code{"BLS"}). Supported
#' options for \code{y_model = "LCSM"} include: \code{"quadratic"} (or \code{"QUAD"}), \code{"negative exponential"}
#' (or \code{"EXP"}), \code{"Jenss-Bayley"} (or \code{"JB"}), and \code{"nonparametric"} (or \code{"NonP"}). It takes the
#' value passed from \code{getMIX()}.
#' @param intrinsic A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the
#' value passed from \code{getMIX()}.
#' @param records A numeric vector specifying the indices of the observed study waves. It takes the value passed from
#' \code{getMIX()}.
#' @param y_model A string specifying how to fit the longitudinal outcome. Supported values are \code{"LGCM"} and \code{"LCSM"}.
#' It takes the value passed from \code{getMIX()}.
#' @param TVC A string specifying the prefix of the column names corresponding to the time-varying covariate at each study wave.
#' It takes the value passed from \code{getMIX()}.
#' @param decompose An integer specifying the decomposition option for temporal states. Supported values include \code{0} (no
#' decomposition), \code{1} (decomposition with interval-specific slopes as temporal states), \code{2} (decomposition with interval-
#' specific changes as temporal states), and \code{3} (decomposition with change-from-baseline as temporal states). It takes the
#' value passed from \code{getMIX()}.
#' @param growth_TIC A string or character vector specifying the column name(s) of time-invariant covariate(s) that account for the
#' variability of growth factors, if any. It takes the value passed from \code{getMIX()}.
#' @param starts A list of initial values for the parameters, either takes the value passed from \code{getMIX()}
#' or derived by the helper function \code{getMIX.initial()}.
#'
#' @return A list of manifest and latent variables and paths for an mxModel object.
#'
#' @keywords internal
#'
#' @importFrom OpenMx mxPath mxModel mxAlgebraFromString mxMatrix mxFitFunctionML
#'
getsub.TVC_l <- function(dat, nClass, t_var, records, y_var, curveFun, intrinsic, y_model, TVC, decompose,
growth_TIC, starts){
## Define manifest variables
manifests <- c(paste0(TVC, records), paste0(y_var, records))
if (!is.null(growth_TIC)){
manifests <- c(manifests, growth_TIC)
}
# Define latent variables for the TVC for each type of decomposition
if (decompose != 0){
X_latents <- c("eta0x", "eta1x", paste0("lx", records), paste0("dx", records[-1]))
if (decompose == 2){
X_latents <- c(X_latents, paste0("deltax", records[-1]))
}
else if (decompose == 3){
X_latents <- c(X_latents, paste0("Deltax", records[-1]))
}
}
TVC_info <- getMIX_TVC.info(nClass = nClass, y_var = y_var, records = records, growth_TIC = growth_TIC, TVC = TVC,
decompose = decompose, starts = starts)
# Obtain factor loadigs for the specified functional form
GF_loadings <- getMIX_UNI.loadings(nClass = nClass, y_model = y_model, t_var = t_var, y_var = y_var,
curveFun = curveFun, intrinsic = intrinsic, records = records)
BETA <- class.list <- list()
## Define latent variables, growth factor loadings, paths of the longitudinal outcome
if (y_model == "LGCM"){
if (curveFun %in% c("linear", "LIN")){
latents <- c("eta0Y", "eta1Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records),
arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("quadratic", "QUAD")){
latents <- c("eta0Y", "eta1Y", "eta2Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records),
arrows = 2, free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"), name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("negative exponential", "EXP")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "deltag")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (decompose == 1){
Y_nGF <- length(latents) - (length(records) * 2 - 1) - 2
}
else if (I(decompose == 2 | decompose == 3)) {
Y_nGF <- length(latents) - (length(records) * 2 - 1) - (length(records) - 1) - 2
}
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
}
else if (curveFun %in% c("Jenss-Bayley", "JB")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y", "deltag")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1),
mxPath(from = "eta1Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2Y", to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
}
else if (curveFun %in% c("bilinear spline", "BLS")){
if (intrinsic){
latents <- c("eta0sY", "eta1sY", "eta2sY", "deltag")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_mean_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_mean_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi0")),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC))"),
name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s", "Y_psi0gs", "Y_psi11s",
"Y_psi12s", "Y_psi1gs", "Y_psi22s", "Y_psi2gs", "Y_psiggs"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = "deltag", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot, 0),",
"cbind(0, 1, -1, 0),",
"cbind(0, 1, 1, 0),",
"cbind(0, 0, 0, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s, c", k, "Y_psi0gs), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s, c", k, "Y_psi1gs), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s, c", k, "Y_psi2gs), ",
"cbind(c", k, "Y_psi0gs, c", k, "Y_psi1gs, c", k, "Y_psi2gs, c", k, "Y_psiggs))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC)"),
name = paste0("c", k, "beta_s")),
mxAlgebraFromString(paste0("rbind(c", k, "func[1:3, 1:3] %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0sY", "eta1sY", "eta2sY")
Y_nGF <- length(latents)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, 1] + c", k, "beta %*% c", k,
"mux"), name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_mean_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_mean_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi0")),
TVC_info[[k]], GF_loadings[[k]], mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta_s")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, 1] + c", k, "beta %*% c", k,
"BL_mean"), name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0s", "Y_mueta1s", "Y_mueta2s"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_knot"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00s", "Y_psi01s", "Y_psi02s",
"Y_psi11s", "Y_psi12s", "Y_psi22s"))),
mxPath(from = "eta0sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records, "[1,1]")),
mxPath(from = "eta2sY", to = paste0(y_var, records), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records, "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "func")),
mxAlgebraFromString(paste0("rbind(cbind(1, -c", k, "Y_knot, c", k, "Y_knot),",
"cbind(0, 1, -1),",
"cbind(0, 1, 1))"), name = paste0("c", k, "grad")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0s, c", k, "Y_mueta1s, c", k, "Y_mueta2s)"),
name = paste0("c", k, "Y_alpha_s")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00s, c", k, "Y_psi01s, c", k, "Y_psi02s), ",
"cbind(c", k, "Y_psi01s, c", k, "Y_psi11s, c", k, "Y_psi12s), ",
"cbind(c", k, "Y_psi02s, c", k, "Y_psi12s, c", k, "Y_psi22s))"),
name = paste0("c", k, "Y_psi_s")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k, "beta2TVC)"),
name = paste0("c", k, "beta_s")),
mxAlgebraFromString(paste0("rbind(c", k, "func %*% c", k,
"Y_alpha_s, c", k, "Y_knot)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "Y_psi_s %*% t(c", k, "grad)"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("c", k, "grad %*% c", k, "beta_s"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 [1:3, 1]+ c", k, "beta %*% c", k,
"X_mueta0"), name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], BETA, mxFitFunctionML(vector = T))
}
}
}
}
}
}
else if (y_model == "LCSM"){
Y_PATH_L_L <- Y_PATH_SLP_L <- Y_PATH_AUTO_L <- list()
for (k in 1:nClass){
## Define paths from latent true scores to observed scores
Y_PATH_L <- mxPath(from = paste0("ly", records), to = paste0(y_var, records), arrows = 1, free = FALSE,
values = 1)
## Define paths from latent instantaneous rate of change at each measurement to true scores
Y_PATH_SLP <- mxPath(from = paste0("dy", records[-1]), to = paste0("ly", records[-1]), arrows = 1,
free = FALSE, values = 0, labels = paste0("lag", records[-1], "[1,1]"))
#### Define autoregressive paths
Y_PATH_AUTO <- mxPath(from = paste0("ly", records[-length(records)]), to = paste0("ly", records[-1]),
arrows = 1, free = FALSE, values = 1)
Y_PATH_L_L[[k]] <- Y_PATH_L
Y_PATH_SLP_L[[k]] <- Y_PATH_SLP
Y_PATH_AUTO_L[[k]] <- Y_PATH_AUTO
}
# Obtain additional parameters (derived) for the specified functional form
AddPara <- getMIX_UNI.addpara(dat = dat, nClass = nClass, curveFun = curveFun, intrinsic = intrinsic,
t_var = t_var, records = records, growth_TIC = growth_TIC, decompose = decompose,
starts = starts)
if (curveFun %in% c("nonparametric", "NonP")){
latents <- c("eta0Y", "eta1Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1,
free = c(F, rep(T, length(records) - 2)), values = c(1, starts[[k]][[1]][[4]][-1]),
labels = paste0("c", k, "Y_rel_rate", 1:(length(records) - 1))),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("quadratic", "QUAD")){
latents <- c("eta0Y", "eta1Y", "eta2Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_mueta2)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (curveFun %in% c("negative exponential", "EXP")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "deltag", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c",
k, "betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"),
name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs",
free = TRUE, values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi0g",
"Y_psi11", "Y_psi1g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE,
values = 0, labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c",
k, "betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 2, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:2, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:2], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:2],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][3],
labels = paste0("c", k, "Y_slp_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:2], to = latents[1:2], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:2, 4)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi11"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L1", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]],
labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k,
"Y_slp_ratio)"), name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:2, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
}
else if (curveFun %in% c("Jenss-Bayley", "JB")){
if (intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y", "deltag", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
BETA[[Y_nGF]] <- mxPath(from = growth_TIC, to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)))))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
BETA[[Y_nGF]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF, ],
labels = paste0("c", k, "beta", "g", c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 4, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:4, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC)),
paste0("c", k, "betagTIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:(Y_nGF - 1)){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
BETA[[Y_nGF]] <- mxPath(from = "lx1", to = latents[Y_nGF], arrows = 1, free = TRUE, values = starts[[k]][[4]][Y_nGF],
labels = paste0("c", k, "beta", "g", "TVC"))
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:4], to = latents[1:4], arrows = 2, connect = "unique.pairs",
free = TRUE,values = starts[[k]][[1]][[2]],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02", "Y_psi0g", "Y_psi11",
"Y_psi12", "Y_psi1g", "Y_psi22", "Y_psi2g", "Y_psigg"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = "deltag", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L3", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02, c", k, "Y_psi0g), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12, c", k, "Y_psi1g), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22, c", k, "Y_psi2g), ",
"cbind(c", k, "Y_psi0g, c", k, "Y_psi1g, c", k, "Y_psi2g, c", k, "Y_psigg))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC, c", k, "betagTVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0 + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
else if (!intrinsic){
latents <- c("eta0Y", "eta1Y", "eta2Y", paste0("dy", records[-1]), paste0("ly", records))
Y_nGF <- length(latents) - (length(records) * 2 - 1)
if (decompose == 0){
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = growth_TIC, to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)))))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "mux"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi0")),
mxPath(from = "one", to = paste0(TVC, records), arrows = 1, free = TRUE,
values = starts[[k]][[2]][[1]], labels = paste0("c", k, "TVC_m", records)),
mxPath(from = paste0(TVC, records), to = paste0(TVC, records), arrows = 2, free = TRUE,
values = starts[[k]][[2]][[2]], labels = paste0("c", k, "TVC_v", records)),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]],
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
else if (decompose != 0){
latents <- c(latents, X_latents)
for (k in 1:nClass){
if (!is.null(growth_TIC)){
nTICs <- length(growth_TIC)
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = c(growth_TIC, "lx1"), to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p, ],
labels = paste0("c", k, "beta", p - 1, c(paste0("TIC", 1:length(growth_TIC)), "TVC")))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxMatrix("Full", 3, length(growth_TIC), free = TRUE,
values = starts[[k]][[4]][1:3, 1:length(growth_TIC)],
labels = c(paste0("c", k, "beta0TIC", 1:length(growth_TIC)),
paste0("c", k, "beta1TIC", 1:length(growth_TIC)),
paste0("c", k, "beta2TIC", 1:length(growth_TIC))),
byrow = T, name = paste0("c", k, "beta_TIC")),
mxAlgebraFromString(paste0("cbind(c", k, "beta_TIC,",
"rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC))"),
name = paste0("c", k, "beta")),
mxMatrix("Full", length(growth_TIC), 1, free = TRUE, starts[[k]][[3]][[1]][1:length(growth_TIC)],
labels = c(paste0("c", k, "mux", 1:length(growth_TIC))),
byrow = F, name = paste0("c", k, "mux")),
mxAlgebraFromString(paste0("rbind(c", k, "mux, c", k, "X_mueta0)"),
name = paste0("c", k, "BL_mean")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "BL_mean"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
else if (is.null(growth_TIC)){
for (p in 1:Y_nGF){
BETA[[p]] <- mxPath(from = "lx1", to = latents[p], arrows = 1, free = TRUE, values = starts[[k]][[4]][p],
labels = paste0("c", k, "beta", p - 1, "TVC"))
}
class.list[[k]] <- mxModel(name = paste0("Class", k), type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = "one", to = latents[1:3], arrows = 1, free = TRUE, values = starts[[k]][[1]][[1]][1:3],
labels = paste0("c", k, c("Y_mueta0", "Y_mueta1", "Y_mueta2"))),
mxMatrix("Full", 1, 1, free = TRUE, values = starts[[k]][[1]][[1]][4],
labels = paste0("c", k, "Y_acc_ratio"), name = paste0("c", k, "Y_mug")),
mxPath(from = latents[1:3], to = latents[1:3], arrows = 2, connect = "unique.pairs", free = TRUE,
values = starts[[k]][[1]][[2]][c(1:3, 5:6, 8)],
labels = paste0("c", k, c("Y_psi00", "Y_psi01", "Y_psi02",
"Y_psi11", "Y_psi12", "Y_psi22"))),
mxPath(from = "eta0Y", to = "ly1", arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta1Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 1),
mxPath(from = "eta2Y", to = paste0("dy", records[-1]), arrows = 1, free = FALSE, values = 0,
labels = paste0("c", k, "L2", records[-1], "[1,1]")),
mxPath(from = paste0(y_var, records), to = paste0(y_var, records), arrows = 2,
free = TRUE, values = starts[[k]][[1]][[3]], labels = paste0("c", k, "Y_residuals")),
mxAlgebraFromString(paste0("rbind(c", k, "Y_mueta0, c", k, "Y_mueta1, c", k, "Y_mueta2, c", k, "Y_acc_ratio)"),
name = paste0("c", k, "Y_alpha0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "Y_psi00, c", k, "Y_psi01, c", k, "Y_psi02), ",
"cbind(c", k, "Y_psi01, c", k, "Y_psi11, c", k, "Y_psi12), ",
"cbind(c", k, "Y_psi02, c", k, "Y_psi12, c", k, "Y_psi22))"),
name = paste0("c", k, "Y_psi_r")),
mxAlgebraFromString(paste0("rbind(c", k, "X_mueta0, c", k, "X_mueta1)"),
name = paste0("c", k, "X_mean0")),
mxAlgebraFromString(paste0("rbind(cbind(c", k, "X_psi00, c", k, "X_psi01),",
"cbind(c", k, "X_psi01, c", k, "X_psi11))"),
name = paste0("c", k, "X_psi0")),
mxAlgebraFromString(paste0("rbind(c", k, "beta0TVC, c", k, "beta1TVC, c", k,
"beta2TVC)"),
name = paste0("c", k, "beta")),
mxAlgebraFromString(paste0("c", k, "Y_alpha0[1:3, ] + c", k, "beta %*% c", k, "X_mueta0"),
name = paste0("c", k, "Y_mean0")),
TVC_info[[k]], GF_loadings[[k]], AddPara[[k]], BETA,
Y_PATH_L_L[[k]], Y_PATH_SLP_L[[k]], Y_PATH_AUTO_L[[k]],
mxFitFunctionML(vector = T))
}
}
}
}
}
}
return(class.list)
}
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