dataNORM01

The <code>data01</code> dataset is a simulated dataset included in the package. It contains
500 trajectories with 10 time-points each, simulating a 3-group solution. The parameters
for the groups are summarized in the table below:
<table class="table">
<tr><td>Parameter</td><td>Group 1</td><td>Group 2</td><td>Group 3</td></tr>
<tr><td>\(\beta_{k0}\)</td><td>2.797</td><td>7.000</td><td>19.545</td></tr>
<tr><td>\(\beta_{k1}\)</td><td>8.809</td><td>-0.297</td><td>-0.407</td></tr>
<tr><td>\(\beta_{k2}\)</td><td>-3.201</td><td>0.463</td><td>0.026</td></tr>
<tr><td>\(\beta_{k3}\)</td><td>0.000</td><td>-0.021</td><td>0.000</td></tr>
<tr><td>\(\pi_k\)</td><td>0.32</td><td>0.54</td><td>0.14</td></tr>
<tr><td>\(\sigma_k\)</td><td>4.000</td><td>4.000</td><td>4.000</td></tr>
</table>

datasets

Estimation of group-based trajectory models, including finite mixture models for longitudinal data,
supporting censored normal, zero-inflated Poisson, logit, and beta distributions,
using expectation-maximization and quasi-Newton methods, with tools for model selection,
diagnostics, and visualization of latent trajectory groups,
<doi:10.4159/9780674041318>, Nagin, D. (2005). Group-Based Modeling of Development. Cambridge, MA: Harvard University Press.
and Noel (2022), <https://orbilu.uni.lu/>, thesis.

Cc3<a9>dric NOEL

trajeR

Group Based Modeling Trajectory

Cédric Noel

Jang Schiltz

dataNORM01 function

A data frame with 500 rows and 43 columns:<dl>
 <dt>Columns 2:11</dt>
<dd>Matrix of real numbers (variable of interest, Y).</dd> <dt>Columns 12:21</dt>
<dd>Matrix of time points (1 to 10, A).</dd> <dt>Columns 22:31</dt>
<dd>Matrix of binary values (0 or 1, time-dependent covariate W).</dd> <dt>Columns 32:41</dt>
<dd>Matrix of real numbers (additional time-dependent covariate W).</dd> <dt>Columns 42:43</dt>
<dd>Matrix of binary values (0 or 1, covariate X).</dd>
</dl>

Format

The <code>data01</code> dataset is a simulated dataset included in the package. It contains
500 trajectories with 10 time-points each, simulating a 3-group solution. The parameters
for the groups are summarized in the table below:
<table class='table'>
<tr><td>Parameter</td><td>Group 1</td><td>Group 2</td><td>Group 3</td></tr>
<tr><td>\(\beta_{k0}\)</td><td>2.797</td><td>7.000</td><td>19.545</td></tr>
<tr><td>\(\beta_{k1}\)</td><td>8.809</td><td>-0.297</td><td>-0.407</td></tr>
<tr><td>\(\beta_{k2}\)</td><td>-3.201</td><td>0.463</td><td>0.026</td></tr>
<tr><td>\(\beta_{k3}\)</td><td>0.000</td><td>-0.021</td><td>0.000</td></tr>
<tr><td>\(\pi_k\)</td><td>0.32</td><td>0.54</td><td>0.14</td></tr>
<tr><td>\(\sigma_k\)</td><td>4.000</td><td>4.000</td><td>4.000</td></tr>
</table>

Simulated CNORM Dataset (data01) — dataNORM01

A data frame with 500 rows and 43 columns:<dl>
 <dt>Columns 2:11</dt>
<dd>Matrix of real numbers (variable of interest, Y).</dd>

 <dt>Columns 12:21</dt>
<dd>Matrix of time points (1 to 10, A).</dd>

 <dt>Columns 22:31</dt>
<dd>Matrix of binary values (0 or 1, time-dependent covariate W).</dd>

 <dt>Columns 32:41</dt>
<dd>Matrix of real numbers (additional time-dependent covariate W).</dd>

 <dt>Columns 42:43</dt>
<dd>Matrix of binary values (0 or 1, covariate X).</dd>


</dl>

dataNORM01: Simulated CNORM Dataset (data01)

Description

Usage

Arguments

Format

Details

Parameter	Group 1	Group 2	Group 3
\(\beta_{k0}\)	2.797	7.000	19.545
\(\beta_{k1}\)	8.809	-0.297	-0.407
\(\beta_{k2}\)	-3.201	0.463	0.026
\(\beta_{k3}\)	0.000	-0.021	0.000
\(\pi_k\)	0.32	0.54	0.14
\(\sigma_k\)	4.000	4.000	4.000