getLCSM.output

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)

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

getLCSM.output function

<dl><dt>model</dt>
<dd>An object representing a fitted latent change score model.</dd>
<dt>curveFun</dt>
<dd>A string specifying the functional form of the growth curve. Supported options for latent change score
models 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>getLCSM()</code>.</dd>
<dt>growth_TIC</dt>
<dd>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 <code>getLCSM()</code>.</dd>
<dt>names</dt>
<dd>A character vector specifying parameter names. It takes the value passed from <code>getLCSM()</code>.</dd></dl>

Arguments

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

<dl>

<dt>model</dt>
<dd>An object representing a fitted latent change score model.</dd>


<dt>curveFun</dt>
<dd>A string specifying the functional form of the growth curve. Supported options for latent change score
models 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>getLCSM()</code>.</dd>


<dt>growth_TIC</dt>
<dd>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 <code>getLCSM()</code>.</dd>


<dt>names</dt>
<dd>A character vector specifying parameter names. It takes the value passed from <code>getLCSM()</code>.</dd>

</dl>

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

Description

Usage

Value

Arguments