- 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 each longitudinal process, and time-invariant covariates (TICs) if any.
- prop_starts
A numeric vector of user-specified initial component proportions of latent classes.
- sub_Model
A string that specifies the sub-model for latent classes. Supported sub-models include "LGCM" (for latent
growth curve models), "LCSM" (for latent change score models), "TVC" (for latent growth curve models or latent change
score models with a time-varying covariate), "MGM" (for multivariate latent growth curve models or latent change score models),
and "MED" (for longitudinal mediation models).
- cluster_TIC
A string or character vector representing the column name(s) for time-invariant covariate(s) indicating cluster
formations. Default is NULL, indicating no such time-invariant covariates are present in the model.
- t_var
A string specifying the prefix of the column names corresponding to the time variable for each study wave.
This applies when sub_Model is "LGCM", "LCSM" or "TVC". For sub_Model being "MGM"
or "MED", t_var should be a string vector where each element corresponds to the time variable prefix for each
respective longitudinal process.
- records
A numeric vector denoting the indices of the observed study waves. This applies when sub_Model is
"LGCM", "LCSM" or "TVC". For sub_Model being "MGM" or "MED", records should
be a list of numeric vectors, where each vector provides the indices of the observed study waves for each longitudinal process.
- y_var
A string defining the prefix of the column names corresponding to the outcome variable for each study wave. This
is applicable when sub_Model is not "MGM". For sub_Model being "MGM", y_var should be a
string vector where each element corresponds to the prefix of the column names for each outcome variable across the study waves.
- curveFun
A string specifying the functional forms of the growth curve(s). 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: "nonparametric" (or "NonP"), "quadratic" (or "QUAD"), "negative exponential"
(or "EXP"), and "Jenss-Bayley" (or "JB").
- intrinsic
A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. By default, this is
NULL as it is unnecessary when sub_Model is "MED".
- y_model
A string that specifies how to fit longitudinal outcomes. Supported values are "LGCM" and "LCSM".
By default, this is NULL as this argument only requires when sub_Model is "TVC" or "MGM".
- m_var
A string that specifies the prefix of the column names corresponding to the mediator variable at each study wave.
By default, this is NULL as this argument only requires when sub_Model is "MED".
- x_type
A string indicating the type of predictor variable used in the model. Supported values are "baseline"
and "longitudinal". By default, this is NULL as this argument only requires when sub_Model is "MED".
- x_var
A string specifying the baseline predictor if x_type = "baseline", or the prefix of the column names
corresponding to the predictor variable at each study wave if x_type = "longitudinal". By default, this is NULL as
this argument only requires when sub_Model is "MED".
- TVC
A string that specifies the prefix of the column names corresponding to the time-varying covariate at each time
point. By default, this is NULL as this argument only requires when sub_Model is "TVC".
- 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). By default, this
is NULL as this argument only requires when sub_Model is "TVC".
- growth_TIC
A string or character vector of column names of time-invariant covariate(s) accounting for the variability
of growth factors if any. Default is NULL, indicating no growth TICs present in the model.
- starts
A list containing initial values for the parameters. Default is NULL, indicating no user-specified
initial values.
- res_scale
A list where each element is a (vector of) numeric scaling factor(s) for residual variance to calculate the
corresponding initial value for a latent class, between 0 and 1 exclusive. By default, this is NULL, as it
is unnecessary when the user specifies the initial values using the starts argument.
- res_cor
A list where each element is a (vector of) numeric initial value(s) for residual correlation in each class. It
needs to be specified if the sub_Model is "TVC" (when decompose != 0), "MGM", or "MED". By default,
this is NULL, as it is unnecessary when the user specifies the initial values using the starts argument.
- tries
An integer specifying the number of additional optimization attempts. Default is NULL.
- OKStatus
An integer (vector) specifying acceptable status codes for convergence. Default is 0.
- jitterD
A string specifying the distribution for jitter. Supported values are: "runif" (uniform
distribution), "rnorm" (normal distribution), and "rcauchy" (Cauchy distribution). Default is "runif".
- loc
A numeric value representing the location parameter of the jitter distribution. Default is 1.
- scale
A numeric value representing the scale parameter of the jitter distribution. Default is 0.25.
- paramOut
A logical flag indicating whether to output the parameter estimates and standard errors. Default is FALSE.
- names
A character vector specifying parameter names. Default is NULL.