getMGM.output: Extract Point Estimates And Standard Errors of Multivariate...

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

Extract Point Estimates And Standard Errors of Multivariate Latent Growth Curve Models Or Multivariate Latent Change Score Models

Description

This function computes and returns a data frame containing point estimates and standard errors for the parameters of a multivariate latent growth curve model or a multivariate latent change score model.

Usage

getMGM.output(model, y_var, records, curveFun, y_model, names)

Arguments

model	An object representing a fitted multivariate latent growth curve model or latent change score model.
y_var	A vector of strings, with each element representing the prefix for column names corresponding to a particular outcome variable at each study wave. It takes the value passed from getMGM().
records	A list of numeric vectors, with each vector specifying the indices of the observed study waves for the corresponding outcome variable. It takes the value passed from getMGM().
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 getMGM().
y_model	A string specifying how to fit the longitudinal outcome. Supported values are "LGCM" and "LCSM". It takes the value passed from getMGM().
names	A character vector specifying parameter names. It takes the value passed from getMGM().

Value

A data frame containing the point estimates and standard errors for parameters of a multivariate latent growth curve model or a multivariate latent change score model.

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