getMIX_TVC.info: Get the Time-Varying Covariate (TVC) Information for a...

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

Get the Time-Varying Covariate (TVC) Information for a Mixture Model or Multiple Group Model with a Time-varying Covariate

Description

This function constructs the OpenMx model paths and parameters for a TVC and its relationship with the parameters related to growth factors of a longitudinal outcome.

Usage

getMIX_TVC.info(nClass, y_var, records, growth_TIC, TVC, decompose, starts)

Arguments

nClass	An integer specifying the number of classes for the mixture model or multiple group model. It takes the value passed from getMIX() or 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 getMIX() or getMGroup().
records	A numeric vector specifying the indices of the observed study waves. It takes the value passed from getMIX() or getMGroup().
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. Default is NULL, indicating no growth TICs present in the model. It takes the value passed from getMIX() or getMGroup().
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 getMIX() or getMGroup().
decompose	An integer specifying the decomposition option for temporal states. Supported values include 0 (no decomposition), 1 (decomposition with interval-specific slopes as temporal states), 2 (decomposition with interval- specific changes as temporal states), and 3 (decomposition with change-from-baseline as temporal states). It takes the value passed from getMIX() or getMGroup().
starts	A list of initial values for the parameters, either takes the value passed from getMIX() or getMGroup(), or derived by the helper function getMIX.initial() or getMGroup.initial().

Value

A list with each sub-list containing a list of OpenMx paths and parameters for the TVC and an OpenMx path for the state effect of the TVC on the corresponding longitudinal outcome.

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