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A meta-analysis combines and compares quantitative results of a set of studies in which more or less the same research question has been investigated. Based on a simple data set, the goals and opportunities of meta-analysis are introduced. It will be shown how a meta-analysis on a set of studies investigating an association between two variables can result in more power and accuracy in testing and estimating the overall size of association. Besides, a meta-analysis offers the possibility to assess study heterogeneity in the association, and to investigate if this heterogeneity can be explained by one or more study characteristics. Next, some common measures of association will be examined, and it will be shown how these can be calculated based on various formats in which study results are typically reported. We will briefly discuss con...
Multilevel models are increasingly used to model the between-study and the sampling variation, and look for moderator variables to explain the between-study variation. A major advantage of using multilevel models for meta-analysis is their amazing flexibility, allowing fitting models that may better match the kind of data and the research questions. One possibility that is seldom mentioned in the methodological meta-analytic literature or typically is not implemented in software for meta-analysis, is the distinction of a third level of variation to model dependencies between studies (e.g., occurring when several studies stem from the same research group) or within studies (e.g., occurring when within a study multiple samples were drawn). In the presentation we try to clarify, using real data examples and a simulation study, in which ...
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