getMGroup.output: Extract Point Estimates And Standard Errors of Longitudinal Multiple Group Models

Description

This function computes and returns a data frame containing point estimates and standard errors for the parameters of a longitudinal multiple group model.

Usage

getMGroup.output(
  model,
  nClass,
  sub_Model,
  y_var,
  curveFun,
  x_type,
  records,
  growth_TIC,
  y_model,
  decompose,
  names
)

Value

A dataframe containing point estimates and standard errors for the parameters of interest for a mixture model.

Arguments

model: An object representing a fitted mixture model.
nClass: An integer specifying the number of latent classes for the mixture model. It takes the value passed from getMGroup().
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). It takes the value passed from getMGroup().
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. It takes the value passed from getMGroup().
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 getMGroup().
x_type: A string indicating the type of predictor variable used in the model. Supported values are "baseline" and "longitudinal". It takes the value passed from getMGroup().
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. It takes the value passed from getMGroup().
growth_TIC: A string or character vector of column names of time-invariant covariate(s) accounting for the variability of growth factors if any. It takes the value passed from getMGroup().
y_model: A string that specifies how to fit longitudinal outcomes. Supported values are "LGCM" and "LCSM". It takes the value passed from getMGroup().
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 getMGroup().
names: A character vector specifying parameter names. It takes the value passed from getMGroup().