This function defines latent growth curve models as class-specific models (submodels) for a longitudinal mixture model.
getsub.LGCM_l(
dat,
nClass,
t_var,
records,
y_var,
curveFun,
intrinsic,
growth_TIC,
starts
)
A list of manifest and latent variables and paths for an mxModel object.
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()
.
An integer specifying the number of latent classes for the mixture model. It takes the value passed from getMIX()
.
A string specifying the prefix of the column names corresponding to the time variable at each study wave.
It takes the value passed from getMIX()
.
A numeric vector specifying indices of the study waves. It takes the value passed from getMIX()
.
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()
.
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 getMIX()
.
A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the value
passed from getMIX()
.
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 getMIX()
.
A list of initial values for the parameters, either takes the value passed from getMIX()
or
derived by the helper function getMIX.initial()
.