Comparison of Weights for Meta-Analysis of r and d Under Realistic Conditions
Document Type
Article
Publication Date
2011
Keywords
computer simulation procedures (e.g., Monte Carlo, bootstrapping), meta-analysis, sampling
Digital Object Identifier (DOI)
https://doi.org/10.1177%2F1094428110368725
Abstract
We compared unit, sample size, and inverse variance weighting procedures for estimating the overall mean and random-effects variance component (REVC) in random-effects meta-analysis under realistic conditions for both r and d. Root mean square error and average absolute error of estimation were used to compare weighting schemes via Monte-Carlo simulation. For r, unit weights worked surprisingly well, and sample size weights worked best overall. For d, unit weights worked poorly, and inverse variance weights worked best overall. Discussion focuses on the meta-analyst’s choice of weights, possible explanations for the differences across types of effect size, and implications for meta-analytic inferences in organizational research.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Organizational Research Methods, v. 14, issue 4, p. 587-607
Scholar Commons Citation
Brannick, Michael T.; Yang, Liu-Qin; and Cafri, Guy, "Comparison of Weights for Meta-Analysis of r and d Under Realistic Conditions" (2011). Psychology Faculty Publications. 2302.
https://digitalcommons.usf.edu/psy_facpub/2302
