getMIX.output: Extract Point Estimates And Standard Errors of Longitudinal...

In nlpsem: Linear and Nonlinear Longitudinal Process in Structural Equation Modeling Framework

Extract Point Estimates And Standard Errors of Longitudinal Mixture Models

Description

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

Usage

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

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 getMIX().
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 getMIX().
cluster_TIC	A string or character vector representing the column name(s) for time-invariant covariate(s) indicating cluster formations. It takes the value passed from getMIX().
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 getMIX().
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 getMIX().
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 getMIX().
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 getMIX().
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 getMIX().
y_model	A string that specifies how to fit longitudinal outcomes. Supported values are "LGCM" and "LCSM". It takes the value passed from getMIX().
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 getMIX().
names	A character vector specifying parameter names. It takes the value passed from getMIX().

Value

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

nlpsem documentation built on Sept. 13, 2023, 1:06 a.m.