getMGM.mxModel: Construct An Object of mxModel for Multivariate Latent Growth Curve Models or Multivariate Latent Change Score Models To Be Evaluated

Description

This function builds up an object of mxModel for a multivariate latent growth curve model or a multivariate latent change score model with user-specified functional form (including whether intrinsically nonlinear).

Usage

getMGM.mxModel(
  dat,
  t_var,
  y_var,
  curveFun,
  intrinsic,
  records,
  y_model,
  starts
)

Value

A pre-optimized mxModel for a multivariate latent growth curve model or a multivariate latent change score model.

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 multiple longitudinal outcomes. It takes the value passed from getMGM().
t_var: A vector of strings, with each element representing the prefix for column names related to the time variable for the corresponding outcome variable at each study wave. It takes the value passed from getMGM().
y_var: A vector of strings, with each element representing the prefix for column names corresponding to a particular outcome variable at each study wave. It takes the value passed from getMGM().
curveFun: A string specifying the functional form of the growth curve. Supported options for y_model = "LGCM" include: "linear" (or "LIN"), "quadratic" (or "QUAD"), "negative exponential" (or "EXP"), "Jenss-Bayley" (or "JB"), and "bilinear spline" (or "BLS"). Supported options for y_model = "LCSM" include: "quadratic" (or "QUAD"), "negative exponential" (or "EXP"), "Jenss-Bayley" (or "JB"), and "nonparametric" (or "NonP"). It takes the value passed from getMGM().
intrinsic: A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the value passed from getMGM().
records: A list of numeric vectors, with each vector specifying the indices of the observed study waves for the corresponding outcome variable. It takes the value passed from getMGM().
y_model: A string specifying how to fit the longitudinal outcome. Supported values are "LGCM" and "LCSM". It takes the value passed from getMGM().
starts: A list of initial values for the parameters, either takes the value passed from getMGM() or derived by the helper function getMULTI.initial().