Effect Sizes for Single Case Experimental Designs and Their Utility for a Meta-Analysis: A Simulation Study

There has been a lack of consensus as to the optimal effect size for use in meta-analyses involving Single Case Experimental Designs (SCEDs). SCEDs are a set of experimental designs which produce data akin to short interrupted time-series, where observations may not be independent due to autocorrelation. This thesis evaluated the statistical properties of various effect sizes for a reversal ABA'B' SCED via a simulation study. Hedges, Pustejovsky, and Shadishs (2012) Standardized Mean Difference effect size (_HPS) performed best when small to moderate degrees of autocorrelation were present. Partial regression coefficients also performed relatively well in most situations. The results recommend the utilization of _HPS: besides its favorable performance, _HPS has also been designed to be comparable to group-based effect sizes (Cohens d) thus enabling the amalgamation of both SCEDs and group designs in a meta-analysis. Partial regression coefficients may also be used effectively in a meta-analysis of results from SCEDs.