Effect Size Metrics and Pooling Methods
This chapter covers the meanings and measures of effect size (ES), focusing on common effect size measures. Confidence intervals are used to capture the precision of ES estimates. Corrections for clustering, dependencies, and other problems are considered. The use of Forrest plots and different pooling methods are described. Finally, measures of heterogeneity of effects across studies — and ways to handle this heterogeneity — are explored.
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