getLGCM.mxModel function

Construct An Object of mxModel for Latent Growth Curve Model with Time-invariant Covariates (If Any) To Be Evaluated

his function builds up an object of mxModel for a latent growth curve model with user-specified functional form (including whether intrinsically nonlinear) with time-invariant covariates (if any).

getLGCM.mxModel(
  dat,
  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, and time-invariant covariates (TICs) if any. It takes the value passed from getLGCM().

• 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 getLGCM().

• 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 getLGCM().

• curveFun: A string specifying the functional form of the growth curve. Supported options for latent growth curve models are: "linear" (or "LIN"), "quadratic" (or "QUAD"), "negative exponential"

  (or "EXP"), "Jenss-Bayley" (or "JB"), and "bilinear spline" (or "BLS"). It takes the value passed from getLGCM().

• intrinsic: A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the value passed from getLGCM().

• records: A numeric vector specifying indices of the study waves. It takes the value passed from getLGCM().

• 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 getLGCM().

• starts: A list containing initial values for the free parameters, either takes the value passed from getLGCM() or derived by the helper function getUNI.initial().

Returns

A pre-optimized mxModel for a Latent Growth Curve Model.