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

Terri Pigott, Georgia State University
Researchers looking at data

Education research has faced serious criticism for decades about its failure to accumulate knowledge over time and these criticisms garnered enough attention to shape federal policy.

Toward the goal of more rapid knowledge accumulation via better meta-analyses, this article, published in Educational Researcher, 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.