Testing Categorical Moderators in Mixed-Effects Meta-analysis in the Presence of Heteroscedasticity

Maria Rubio-Aparicio, Jose A Lopez-Lopez, Wolfgang Viechtbauer, Fulgencio Marín-Martínez, Juan Botella, Julio Sánchez-Meca

Research output: Contribution to journalArticle (Academic Journal)peer-review

18 Citations (Scopus)
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Mixed-effects models can be used to examine the association between a categorical moderator and the magnitude of the effect size. Two approaches are available to estimate the residual between-studies variance, s 2res —namely, separate estimation within each category of the moderator versus pooled estimation across all categories. We examine, by means of a Monte Carlo simulation study, both approaches for s 2res estimation in combination with two methods, the Wald-type X 2 and F tests, to test the statistical significance of the moderator. Results suggest that the F test using a pooled estimate of s 2res across categories is the best option in most conditions, although the F test using separate estimates of s 2res is preferable if the residual heterogeneity variances are heteroscedastic.

Original languageEnglish
Number of pages24
JournalJournal of Experimental Education
Early online date30 Jan 2019
Publication statusE-pub ahead of print - 30 Jan 2019


  • Meta-analysis
  • mixed-effects model
  • residual between-studies variance
  • subgroup analyses


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