achievement

Simulated dataset containing the score on four achievement tests for 50 childrens attending the last year of primary school. The four tests are repeated five times at regular time intervals.

Estimation and analysis of group-based multivariate trajectory models (Nagin, 2018 <doi:10.1177/0962280216673085>; Magrini, 2022 <doi:10.1007/s10182-022-00437-9>). The package implements an Expectation-Maximization (EM) algorithm allowing unbalanced panel and missing values, and provides several functionalities for prediction and graphical representation.

Alessandro Magrini

gbmt

Group-Based Multivariate Trajectory Modeling

achievement function

A data.frame with a total of 250 observations on the following 6 variables:<dl>
 <dt><code>id</code></dt>
<dd>Child identifier.</dd> <dt><code>time</code></dt>
<dd>Assessment time (1 to 5).</dd> <dt><code>speaking</code></dt>
<dd>Score on speaking test (1=minimum, 5=maximum).</dd> <dt><code>reading</code></dt>
<dd>Score on reading test (1=minimum, 5=maximum).</dd> <dt><code>writing</code></dt>
<dd>Score on writing test (1=minimum, 5=maximum).</dd> <dt><code>math</code></dt>
<dd>Score on math test (1=minimum, 5=maximum).</dd> 
</dl>

Format

Achievement tests for children — achievement

A data.frame with a total of 250 observations on the following 6 variables:<dl>
 <dt><code>id</code></dt>
<dd>Child identifier.</dd>

 <dt><code>time</code></dt>
<dd>Assessment time (1 to 5).</dd>

 <dt><code>speaking</code></dt>
<dd>Score on speaking test (1=minimum, 5=maximum).</dd>

 <dt><code>reading</code></dt>
<dd>Score on reading test (1=minimum, 5=maximum).</dd>

 <dt><code>writing</code></dt>
<dd>Score on writing test (1=minimum, 5=maximum).</dd>

 <dt><code>math</code></dt>
<dd>Score on math test (1=minimum, 5=maximum).</dd>

 
</dl>

achievement: Achievement tests for children

Description

Usage

Arguments

Format

See Also