Meta-Analysis With Complex Research Designs: Dealing With Dependence From Multiple Measures and Multiple Group Comparisons

Resource type
Journal Article
Authors/contributors
Title
Meta-Analysis With Complex Research Designs: Dealing With Dependence From Multiple Measures and Multiple Group Comparisons
Abstract
Previous research has shown that treating dependent effect sizes as independent inflates the variance of the mean effect size and introduces bias by giving studies with more effect sizes more weight in the meta-analysis. This article summarizes the different approaches to handling dependence that have been advocated by methodologists, some of which are more feasible to implement with education research studies than others. A case study using effect sizes from a recent meta-analysis of reading interventions is presented to compare the results obtained from different approaches to dealing with dependence. Overall, mean effect sizes and variance estimates were found to be similar, but estimates of indexes of heterogeneity varied. Meta-analysts are advised to explore the effect of the method of handling dependence on the heterogeneity estimates before conducting moderator analyses and to choose the approach to dependence that is best suited to their research question and their data set.
Publication
Review of Educational Research
Volume
84
Issue
3
Pages
328-364
Date
09/2014
Journal Abbr
Review of Educational Research
Language
en
ISSN
0034-6543, 1935-1046
Short Title
Meta-Analysis With Complex Research Designs
Accessed
01/11/2023, 23:22
Library Catalogue
DOI.org (Crossref)
Citation
Scammacca, N., Roberts, G., & Stuebing, K. K. (2014). Meta-Analysis With Complex Research Designs: Dealing With Dependence From Multiple Measures and Multiple Group Comparisons. Review of Educational Research, 84(3), 328–364. https://doi.org/10.3102/0034654313500826