Bridging SCED and Group Designs: Demonstrating the Ratio-Metric BC-IRR Effect Size in a Meta-Analysis

<title>Abstract</title> <p>This study introduces the between-case incidence rate ratio (BC-IRR), a ratio-metric effect size for single-case experimental designs (SCEDs), and demonstrates its use in a reanalysis of Barton et al.’s (2017) meta-analysis of technology-aided instruction and intervention (TAII) for students with autism spectrum disorder (ASD). We applied generalized estimating equation (GEE) models to estimate BC-IRR for SCED outcomes and computed mean response ratios for group designs. Across 36 eligible outcomes (29 from five group-design studies and 8 from eight SCED studies), separate random-effects models showed that group-design studies yielded a pooled mean response ratio of 1.23 (95% CI [1.00, 1.52]), indicating approximately 23% higher positive outcomes under TAII relative to comparison conditions, whereas SCEDs produced a pooled BC-IRR of 4.52 (95% CI [1.71, 11.92]), indicating more than a fourfold increase over baseline. We discuss BC-IRR’s advantages over BC-SMD, namely, its invariance to outcome variance, insensitivity to observation session length, and direct percent-change interpretation, alongside practical limitations, including the requirement of nonzero baselines. These findings illustrate how BC-IRR can support design-comparable, interpretable synthesis of SCED and group-design evidence while underscoring the importance of triangulating ratio-metric and SMD-type effect sizes when evaluating intervention impact.</p>