Bryant2018

Data from a clustered multiple baseline across participants design conducted by
Bryant et al. (2018). The variables are as follows:<ul>
<li><code>Study_ID</code>. Study identifier.</li>
<li><code>school</code>. School identifier.</li>
<li><code>group</code>. Group identifier.</li>
<li><code>case</code>. Student identifier.</li>
<li><code>treatment</code>. Indicator for treatment phase.</li>
<li><code>session</code>. Measurement occasion.</li>
<li><code>session_trt</code>. Measurement occasion times treatment phase.</li>
<li><code>outcome</code>. Texas Early Mathematics Inventory (TEMI-Aim Check) scores.</li>
<li><code>session_c</code>. Measurement occasion centered at the follow-up time.</li>
</ul>

datasets

Provides a set of tools for estimating hierarchical linear
models and effect sizes based on data from single-case designs.
Functions are provided for calculating standardized mean difference effect sizes that
are directly comparable to standardized mean differences estimated from between-subjects randomized experiments,
as described in Hedges, Pustejovsky, and Shadish (2012) <DOI:10.1002/jrsm.1052>;
Hedges, Pustejovsky, and Shadish (2013) <DOI:10.1002/jrsm.1086>;
Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>;
and Chen, Pustejovsky, Klingbeil, and Van Norman (2023) <DOI:10.1016/j.jsp.2023.02.002>.
Includes an interactive web interface.

Bryant2018: Bryant et al. (2018)

Description

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