Abstract
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, -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 estimation in combination with two methods, the Wald-type and F tests, to test the statistical significance of the moderator. Results suggest that the F test using a pooled estimate of across categories is the best option in most conditions, although the F test using separate estimates of is preferable if the residual heterogeneity variances are heteroscedastic.
Original language | English |
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Pages (from-to) | 288-310 |
Number of pages | 23 |
Journal | Journal of Experimental Education |
Volume | 88 |
Issue number | 2 |
Early online date | 7 Aug 2019 |
DOIs | |
Publication status | Published - 3 Feb 2020 |
Keywords
- Meta-analysis
- mixed-effects model
- subgroup analyses
- residual between-studies variance
- EFFECTS META-REGRESSION
- VARIANCE ESTIMATORS
- HETEROGENEITY
- ANOVA