metagroup: Meaningful Grouping of Studies in Meta-Analysis
Performs meaningful subgrouping in a
meta-analysis. This is a two-step process; first, use the iterative
grouping functions (e.g., mgbin(), mgcont() ) to partition studies
into statistically homogeneous clusters based on their effect size
data. Second, use the meaning() function to analyze these new
subgroups and understand their composition based on study-level
characteristics (e.g., country, setting). This approach helps to
uncover hidden structures in meta-analytic data and provide a deeper
interpretation of heterogeneity.
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