The logic of testing categorical moderators is based on the ability to separate this total heterogeneity (Qtotal) into two components, the between-group heterogeneity (Qbetween) and the within-group heterogeneity (Qwithin), such that: The reason for this subscript is to make it explicit that this is the total, overall heterogeneity among all effect sizes. You might have noticed that I have changed the notation of this equation slightly, now giving the subscript “total” to this Q statistic. Given this logic of partitioning heterogeneity, it makes sense to start with the heterogeneity equation (Equation 8.6) from Chapter 8, reproduced here for convenience: In other words, testing categorical moderators in meta-analysis involves comparing groups of studies classified by their status on some categorical moderator. Whereas ANOVA partitions variability in scores across individuals (or other units of analysis) into variability existing between and within groups, categorical moderator analysis in meta-analysis partitions between-study heterogeneity into that between and within groups of studies (Hedges, 1982 Lipsey & Wilson, 2001, pp. The logic of evaluating categorical moderators in meta-analysis parallels the use of ANOVA in primary data analysis. Evaluating the Significance of a categorical Moderator
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