Promoting Knowledge Accumulation About Intervention Effects: Exploring Strategies for Standardizing Statistical Approaches and Effect Size Reporting

Toward the goal of more rapid knowledge accumulation via better meta-analyses, this article explores statistical approaches intended to increase the precision and comparability of effect sizes from education research. The featured estimate of the proposed approach is a standardized mean difference effect size whose numerator is a mean difference that has been adjusted for baseline differences in the outcome measure, at a minimum, and whose denominator is the total variance. The article describes the utility and efficiency of covariate adjustment through baseline measures and the need to standardize effects on a total variance that accounts for variation at multiple levels. As computation of the total variance can be complex in multilevel studies, a shiny application is provided to assist with computation of the total variance and subsequent effect size. Examples are provided for how to interpret and input the required calculator inputs.

Automated summary

This article discusses statistical approaches to improve the precision and comparability of effect sizes in education research through meta-analyses. It focuses on a standardized mean difference effect size adjusted for baseline differences and total variance. The article highlights the utility of covariate adjustment and the importance of standardizing effects on total variance accounting for variation at multiple levels.