British Journal of Mathematical and Statistical Psychology · 2017 · 57 citations · 14 references
Public HealthBiostatisticsEpidemiologic MethodsExperimental DesignMeta-analysisHeterogeneity AssessmentModerator AnalysisSubgroup AnalysisTreatment Effect HeterogeneityCategorical ModeratorsEffect SizeHeterogeneity DecompositionHeterogeneity EstimationMeta-analytic Subgroup AnalysisResidual HeterogeneitySubgroup StructureWithin-study Subgroup Comparisons
Subgroup analyses allow us to examine the influence of a categorical moderator on the effect size in meta‐analysis. We conducted a simulation study using a dichotomous moderator, and compared the impact of pooled versus separate estimates of the residual between‐studies variance on the statistical performance of the Q B (P) and Q B (S) tests for subgroup analyses assuming a mixed‐effects model. Our results suggested that similar performance can be expected as long as there are at least 20 studies and these are approximately balanced across categories. Conversely, when subgroups were unbalanced, the practical consequences of having heterogeneous residual between‐studies variances were more evident, with both tests leading to the wrong statistical conclusion more often than in the conditions with balanced subgroups. A pooled estimate should be preferred for most scenarios, unless the residual between‐studies variances are clearly different and there are enough studies in each category to obtain precise separate estimates.
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