getTVC.mxModel: Construct An Object of mxModel for Latent Growth Curve Models or Latent Change Score Models with a Time Varying Covariate and Time-invariant Covariates (If Any) To Be Evaluated

Description

This function builds up an object of mxModel for a latent growth curve model or latent change score model with user-specified functional form (including whether intrinsically nonlinear), time-varying covariate, and with time-invariant covariates (if any).

Usage

getTVC.mxModel(
  dat,
  t_var,
  y_var,
  curveFun,
  intrinsic,
  records,
  y_model,
  TVC,
  decompose,
  growth_TIC,
  starts
)

Value

A pre-optimized mxModel for a latent growth curve model or a latent change score model with a time-varying covariate and time-invariant covariates (if any).

Arguments

dat: A wide-format data frame, with each row corresponding to a unique ID. It contains the observed variables with repeated measurements (for the longitudinal outcome and time-varying covariates), occasions, and time-invariant covariates (TICs) if any. It takes the value passed from getTVCmodel().
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 getTVCmodel().
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 getTVCmodel().
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 getTVCmodel().
intrinsic: A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the value passed from getTVCmodel().
records: A numeric vector specifying the indices of the observed study waves. It takes the value passed from getTVCmodel().
y_model: A string specifying how to fit the longitudinal outcome. Supported values are "LGCM" and "LCSM". It takes the value passed from getTVCmodel().
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 getTVCmodel().
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 getTVCmodel().
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 getTVCmodel().
starts: A list of initial values for the parameters, either takes the value passed from getTVCmodel() or derived by the helper function getTVC.initial().