getLCSM.output: Extract Point Estimates And Standard Errors of Latent Change...

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

Extract Point Estimates And Standard Errors of Latent Change Score Model with Time-invariant Covariates (If Any)

Description

This function computes and returns a data frame containing point estimates and standard errors for the parameters of a latent change score model with time-invariant covariates (if any)

Usage

getLCSM.output(model, curveFun, growth_TIC, names)

Arguments

model	An object representing a fitted latent change score model.
curveFun	A string specifying the functional form of the growth curve. Supported options for latent change score models include: "quadratic" (or "QUAD"), "negative exponential" (or "EXP"), "Jenss-Bayley" (or "JB"), and "nonparametric" (or "NonP"). It takes the value passed from getLCSM().
growth_TIC	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 getLCSM().
names	A character vector specifying parameter names. It takes the value passed from getLCSM().

Value

A data frame containing the point estimates and standard errors for parameters of a latent change score model with time-invariant covariates (if any).

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