Correcting effect sizes computed from factorial analysis of variance for use in meta-analysis

In meta-analysis, it is possible to average results across multiple studies because the effect sizes estimated from each study are in the same metric (e.g., the standardized mean difference). However, when effect sizes are computed from a factorial analysis of variance, these estimates are influenced by the other factors in the design. A correction developed by G. V. Glass, B. McGaw, and M. L. Smith (1981) solves this problem; however, it requires information (e.g., sums of squares) that is often not available in published research. A reformulated version of the correction is presented, which requires only F values and degrees of freedom. The impact of the correction on effect size estimates is examined.