getsub.MED_l: Define Longitudinal Mediation Models as Class-specific Models...

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

Define Longitudinal Mediation Models as Class-specific Models (Submodels) for a Longitudinal Mixture Model

Description

This function defines longitudinal mediation models as class-specific models (submodels) for a longitudinal mixture model.

Usage

getsub.MED_l(
  dat,
  nClass,
  t_var,
  records,
  y_var,
  curveFun,
  m_var,
  x_var,
  x_type,
  starts,
  res_cor
)

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 getMIX().
nClass	An integer specifying the number of latent classes for the mixture model. It takes the value passed from getMIX().
t_var	A vector of strings, with each element representing the prefix for column names related to the time variable for the corresponding longitudinal variable at each study wave. It takes the value passed from getMIX().
records	A list of numeric vectors, with each vector specifying the indices of the observed study waves for the corresponding longitudinal variable. It takes the value passed from getMIX().
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 getMIX().
curveFun	A string specifying the functional form of the growth curve. Supported options include: "linear" (or "LIN"), and "bilinear spline" (or "BLS"). It takes the value passed from getMIX().
m_var	A string specifying the prefix of the column names corresponding to the mediator variable at each study wave. It takes the value passed from getMIX().
x_var	A string specifying the baseline predictor if x_type = "baseline", or the prefix of the column names corresponding to the predictor variable at each study wave if x_type = "longitudinal". It takes the value passed from getMIX().
x_type	A string indicating the type of predictor variable used in the model. Supported values are "baseline" and "longitudinal". It takes the value passed from getMIX().
starts	A list of initial values for the parameters, either takes the value passed from getMIX() or derived by the helper function getMIX.initial().
res_cor	A numeric value or vector for user-specified residual correlation between any two longitudinal processes to calculate the corresponding initial value. It takes the value passed from getMIX().

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.