getsub.LCSM_m: Define Latent Change Score Models as Class-specific Models...

In nlpsem: Linear and Nonlinear Longitudinal Process in Structural Equation Modeling Framework

Define Latent Change Score Models as Class-specific Models (Submodels) for a Longitudinal Multiple Group Model

Description

This function defines latent change score models as class-specific models (submodels) for a longitudinal multiple group model.

Usage

getsub.LCSM_m(
  dat,
  nClass,
  grp_var,
  t_var,
  y_var,
  curveFun,
  intrinsic,
  records,
  growth_TIC,
  starts
)

Arguments

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 getMGroup().
nClass	An integer specifying the number of manifested classes for the multiple group model. It takes the value passed from getMGroup().
grp_var	A string specifying the column that indicates manifested classes. It takes the value passed from getMGroup().
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 getMGroup().
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 getMGroup().
curveFun	A string specifying the functional form of the growth curve. Supported options for latent change score models include: "quadratic" (or "QUAD"), "negative exponential" (or "EXP"), "Jenss-Bayley" (or "JB"), and "nonparametric" (or "NonP"). It takes the value passed from getMGroup().
intrinsic	A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the value passed from getMGroup().
records	A numeric vector specifying indices of the study waves. It takes the value passed from getMGroup().
growth_TIC	A string or character vector specifying the column name(s) of time-invariant covariate(s) contributing to the variability of growth factors if any. It takes the value passed from getMGroup().
starts	A list of initial values for the parameters, either takes the value passed from getMGroup() or derived by the helper function getMGroup.initial().

Value

A list of manifest and latent variables and paths for an mxModel object.

nlpsem documentation built on Sept. 13, 2023, 1:06 a.m.