symptoms

A simulated, longitudinal dataset capturing symptom severity with an arbitrary scale (total score: 0-28), over a 2-year follow-up
period for 350 individuals. The data is not normally distributed and exhibits heterogeneity, including latent (unobserved) trajectories
of symptom severity that reflect diverse progression patterns across individuals. The dataset contains no missing data.

datasets

Provide a suite of functions for conducting and automating Latent Growth Modeling (LGM) in 'Mplus', including Growth Curve Model (GCM), Growth-Based Trajectory Model (GBTM) and Latent Class Growth Analysis (LCGA).
The package builds upon the capabilities of the 'MplusAutomation' package (Hallquist & Wiley, 2018) to streamline large-scale latent variable analyses.
“MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus.” Structural Equation Modeling, 25(4), 621–638. <doi:10.1080/10705511.2017.1402334>
The workflow implemented in this package follows the recommendations outlined in Van Der Nest et al. (2020).
“An Overview of Mixture Modeling for Latent Evolutions in Longitudinal Data: Modeling Approaches, Fit Statistics, and Software.” Advances in Life Course Research, 43, Article 100323. <doi:10.1016/j.alcr.2019.100323>.

Olivier Percie du Sert

MplusLGM

Automate Latent Growth Mixture Modelling in 'Mplus'

Joshua Unrau

symptoms function

A dataframe with 1 row per individual, 350 observations and 10 variables.
<dl>
<dt>id</dt>
<dd>Individual identifier, numeric.</dd><dt>sx_0</dt>
<dd>Symptoms severity at month 0, numeric.</dd><dt>sx_3</dt>
<dd>Symptoms severity at month 3, numeric.</dd><dt>sx_6</dt>
<dd>Symptoms severity at month 6, numeric.</dd><dt>sx_9</dt>
<dd>Symptoms severity at month 9, numeric.</dd><dt>sx_12</dt>
<dd>Symptoms severity at month 12, numeric.</dd><dt>sx_15</dt>
<dd>Symptoms severity at month 15, numeric.</dd><dt>sx_18</dt>
<dd>Symptoms severity at month 18, numeric.</dd><dt>sx_21</dt>
<dd>Symptoms severity at month 21, numeric.</dd><dt>sx_24</dt>
<dd>Symptoms severity at month 24, numeric.</dd>
</dl>

Format

Symptoms Data — symptoms

A dataframe with 1 row per individual, 350 observations and 10 variables.
<dl>
<dt>id</dt>
<dd>Individual identifier, numeric.</dd>

<dt>sx_0</dt>
<dd>Symptoms severity at month 0, numeric.</dd>

<dt>sx_3</dt>
<dd>Symptoms severity at month 3, numeric.</dd>

<dt>sx_6</dt>
<dd>Symptoms severity at month 6, numeric.</dd>

<dt>sx_9</dt>
<dd>Symptoms severity at month 9, numeric.</dd>

<dt>sx_12</dt>
<dd>Symptoms severity at month 12, numeric.</dd>

<dt>sx_15</dt>
<dd>Symptoms severity at month 15, numeric.</dd>

<dt>sx_18</dt>
<dd>Symptoms severity at month 18, numeric.</dd>

<dt>sx_21</dt>
<dd>Symptoms severity at month 21, numeric.</dd>

<dt>sx_24</dt>
<dd>Symptoms severity at month 24, numeric.</dd>


</dl>

symptoms: Symptoms Data

Description

Usage

Arguments

Format