getTVC.initial function

Compute Initial Values for Parameters of Latent Growth Curve Models or Latent Change Score Models with a Time-varying Covariate and Time-invariant Covariates (if any)

This function computes the initial values of the parameters for a latent growth curve model or a latent change score model with a time-varying covariate and time-invariant covariates (if any).

getTVC.initial(
  dat,
  t_var,
  y_var,
  curveFun,
  records,
  growth_TIC,
  TVC,
  decompose,
  res_scale,
  res_cor
)

Arguments

• dat: A wide-format data frame, with each row corresponding to a unique ID. It contains the observed variables with repeated measurements (for the longitudinal outcome and time-varying covariates), occasions, and time-invariant covariates (TICs) if any. It takes the value passed from 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 getTVCmodel().

• y_var: A string specifying the prefix of the column names corresponding to the outcome variable at each study wave. It takes the value passed from getTVCmodel().

• 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 getTVCmodel().

• records: A numeric vector specifying the indices of the observed study waves. It takes the value passed from getTVCmodel().

• growth_TIC: A string or character vector specifying the column name(s) of time-invariant covariate(s) that account for the variability of growth factors, if any. It takes the value passed from getTVCmodel().

• TVC: A string specifying the prefix of the column names corresponding to the time-varying covariate at each study wave. It takes the value passed from 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().

• res_scale: A numeric value or numeric vector. For a model with decompose = 0, it is a numeric value representing the scaling factor used to calculate the initial value for the residual variance of the longitudinal outcome. In cases where decompose != 0, it is a numeric vector of user-specified scaling factors used to calculate the initial values for the residual variance of both the longitudinal outcome and the time-varying covariate. It takes the value passed from getTVCmodel().

• res_cor: A numeric value. When decompose != 0, this represents the user-specified residual correlation between the longitudinal outcome and the time-varying covariate, which is used to calculate the corresponding initial value. If decompose = 0, this should be NULL. It takes the value passed from getTVCmodel().

Returns

A list containing the initial values for parameters related to growth factors, TVC, TICs (if any), and path coefficients (if any) for a latent growth curve model or a latent change score model with a time-varying covariate and time-invariant covariates (if any).