getUNI.GF: Derive Individual Growth Factors for Latent Growth Curve...

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

Derive Individual Growth Factors for Latent Growth Curve Models or Latent Change Score Models with Time-Invariant Covariates (If Any)

Description

This function derives individual growth factors for the specified latent growth curve model or latent change score model from raw data. These individual growth factors help further compute initial values for parameters related to growth factors, time-invariant covariates (if any), and path coefficients (if any).

Usage

getUNI.GF(dat_traj, dat_time, nT, curveFun)

Arguments

dat_traj	A data frame containing the records for the repeated measurements.
dat_time	A data frame containing the records for measurement occasions associated with the repeated measurements.
nT	An integer representing the number of repeated measurements.
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 getUNI.initial() or getMULTI.initial() or getTVC.initial() or getMIX.initial().

Value

A data frame containing the derived individual growth factors from the raw data.

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