getUNI.GF

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).

internal

Provides computational tools for nonlinear longitudinal models, in particular the intrinsically nonlinear models, in four scenarios: (1) univariate longitudinal processes with growth factors, with or without covariates including time-invariant covariates (TICs) and time-varying covariates (TVCs); (2) multivariate longitudinal processes that facilitate the assessment of correlation or causation between multiple longitudinal variables; (3) multiple-group models for scenarios (1) and (2) to evaluate differences among manifested groups, and (4) longitudinal mixture models for scenarios (1) and (2), with an assumption that trajectories are from multiple latent classes. The methods implemented are introduced in Jin Liu (2023) <arXiv:2302.03237v2>.

Jin Liu

nlpsem

Linear and Nonlinear Longitudinal Process in Structural Equation
Modeling Framework

getUNI.GF function

<dl><dt>dat_traj</dt>
<dd>A data frame containing the records for the repeated measurements.</dd>
<dt>dat_time</dt>
<dd>A data frame containing the records for measurement occasions associated with the repeated
measurements.</dd>
<dt>nT</dt>
<dd>An integer representing the number of repeated measurements.</dd>
<dt>curveFun</dt>
<dd>A string specifying the functional form of the growth curve. Supported options for <code>y_model =
"LGCM"</code> include: <code>"linear"</code> (or <code>"LIN"</code>), <code>"quadratic"</code> (or <code>"QUAD"</code>), <code>"negative exponential"</code>
(or <code>"EXP"</code>), <code>"Jenss-Bayley"</code> (or <code>"JB"</code>), and <code>"bilinear spline"</code> (or <code>"BLS"</code>). Supported
options for <code>y_model = "LCSM"</code> include: <code>"quadratic"</code> (or <code>"QUAD"</code>), <code>"negative exponential"</code>
(or <code>"EXP"</code>), <code>"Jenss-Bayley"</code> (or <code>"JB"</code>), and <code>"nonparametric"</code> (or <code>"NonP"</code>). It takes the
value passed from <code>getUNI.initial()</code> or <code>getMULTI.initial()</code> or <code>getTVC.initial()</code> or <code>getMIX.initial()</code>.</dd></dl>

Arguments

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

<dl>

<dt>dat_traj</dt>
<dd>A data frame containing the records for the repeated measurements.</dd>


<dt>dat_time</dt>
<dd>A data frame containing the records for measurement occasions associated with the repeated
measurements.</dd>


<dt>nT</dt>
<dd>An integer representing the number of repeated measurements.</dd>


<dt>curveFun</dt>
<dd>A string specifying the functional form of the growth curve. Supported options for <code>y_model =
"LGCM"</code> include: <code>"linear"</code> (or <code>"LIN"</code>), <code>"quadratic"</code> (or <code>"QUAD"</code>), <code>"negative exponential"</code>
(or <code>"EXP"</code>), <code>"Jenss-Bayley"</code> (or <code>"JB"</code>), and <code>"bilinear spline"</code> (or <code>"BLS"</code>). Supported
options for <code>y_model = "LCSM"</code> include: <code>"quadratic"</code> (or <code>"QUAD"</code>), <code>"negative exponential"</code>
(or <code>"EXP"</code>), <code>"Jenss-Bayley"</code> (or <code>"JB"</code>), and <code>"nonparametric"</code> (or <code>"NonP"</code>). It takes the
value passed from <code>getUNI.initial()</code> or <code>getMULTI.initial()</code> or <code>getTVC.initial()</code> or <code>getMIX.initial()</code>.</dd>

</dl>

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

Description

Usage

Value

Arguments