Requivalent, Meta-Analysis, And Robustness: An Empirical Examination Of Rosenthal And Rubin's Effect Size Indicator
Computer simulation, Effect size, Meta-analysis, Normal distribution
Educational and Psychological Measurement
Rosenthal and Rubin introduced a general effect size index, r equivalent, for use in meta-analyses of two-group experiments; it employs p values from reports of the original studies to determine an equivalent t test and the corresponding point-biserial correlation coefficient. The present investigation used Monte Carlo-simulated meta-analyses to examine the impact on r equivalent effect sizes of research using independent-groups, pooled-variance t tests with that using a less powerful median test. As expected, estimates based on t were higher. These differences were consistent even in the presence of strong variance heterogeneity when data were distributed normally, but not when data were nonnormal. The results suggested that the use of r equivalent be confined to combining studies using inferential tests with comparable power and robustness; they also cast doubt on the use of r equivalent when data are not distributed normally. © 2008 Sage Publications.
Department of Psychology
Original Publication Date
DOI of published version
Gilpin, Andrew R., "Requivalent, Meta-Analysis, And Robustness: An Empirical Examination Of Rosenthal And Rubin's Effect Size Indicator" (2008). Faculty Publications. 2521.