Critical Assumptions and Distribution Features Pertaining to Contemporary Single-Case Effect Sizes

The use of single-case effect sizes (SCESs) has increased in the intervention literature. Meta-analyses based on single-case data have also increased in popularity. However, few researchers who have adopted these metrics have provided an adequate rationale for their selection. We review several important statistical assumptions that should be considered prior to calculating and interpreting SCESs. We then more closely investigate a sampling of these newer procedures and conclude with critical analysis of the potential utility of these metrics.