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

By María Rubio-Aparicio, J. López-López, W. Viechtbauer, Fulgencio Marín-Martínez, J. Botella, J. Sánchez-Meca. Journal of Experimental Education, 2019

56 citations recorded by the source corpus.

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.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f70a8cf5d44222ee2ec335a050606356c2ff7eb8