getUNI.addpara: Get Additional Parameters Related to Interval-specific Slopes, Interval-specific Changes and Values of Change-from-baseline for Latent Change Score Models for Longitudinal Outcome

Description

This function derives additional parameters for latent change score models. In particular, it specifies the means and variances of interval-specific slopes, interval-specific changes, and values of change- from-baseline.

Usage

getUNI.addpara(
  dat,
  curveFun,
  intrinsic = NULL,
  t_var,
  records,
  growth_TIC,
  decompose,
  starts
)

Value

A list containing the specification of the means and variances of interval-specific slopes, interval-specific changes, and values of change-from-baseline for latent change score models.

Arguments

dat: A wide-format data frame, with each row corresponding to a unique ID. It contains the observed variables with repeated measurements and occasions, and time-invariant covariates (TICs) if any. It takes the value passed from getLCSM() or getTVCmodel().
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() or getTVCmodel().
intrinsic: A logical flag indicating whether to build an intrinsically nonlinear longitudinal model. It takes the value passed from getLCSM() or getTVCmodel().
t_var: A string specifying the prefix of the column names corresponding to the time variable at each study wave. It takes the value passed from getLCSM() or getTVCmodel().
records: A numeric vector specifying indices of the study waves. It takes the value passed from getLCSM() or getTVCmodel().
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() or getTVCmodel().
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 getTVCmodel(). The argument is set as NULL when fitting a latent change score model.
starts: A list containing initial values for the parameters, either takes the value passed from getLCSM() or getTVCmodel(), or derived by the helper function getUNI.initial() or getTVC.initial().