Compiled single- and multilevel design parameter database and OSF repository with R scripts and interactive Excel workbooks for RT study planning¶
Product or Programme · All products and programmes
Evidence · 3 claims (3 for) · 1 study (1 quant-synthesis),q3· 0 of 1 report an effect size · 3 claims rest on one study
Description¶
A Stallasch et al. research dataset and repository compiling empirical, meta-analytic, and simulated design parameters for planning randomized achievement studies, with R scripts, Excel workbooks, and the multides package.
Components¶
Claims¶
- The prognostic power of domain-identical pretests degrades with longer pre-posttest time lags, most strongly at the student level [+W]
- At the school level, domain-identical pretests show exceptional prognostic power from grade 5 onward, but are weaker predictors at the student and classroom levels across the school career [+W]
- Domain-identical pretests are the most powerful single-level covariate type for student achievement, outperforming cross-domain pretests, fluid intelligence, and sociodemographic characteristics [+W]
Related Products and Programmes¶
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Key Sources¶
- Stallasch, S. E., Lüdtke, O., Artelt, C., Hedges, L. V., & Brunner, M. (2024). Single- and Multilevel Perspectives on Covariate Selection in Randomized Intervention Studies on Student Achievement. Educational Psychology Review. https://doi.org/10.1007/s10648-024-09898-7
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
compiled-single-and-multilevel-design-parameter-database-and-osf-repository-with-r-scripts |
title |
Compiled single- and multilevel design parameter database and OSF repository with R scripts and interactive Excel workbooks for RT study planning |
description |
A Stallasch et al. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-19 |
trust |
unverified — no one has confirmed this page's content |
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