![]() Another reason for non-independent effect sizes is that the effect sizes of the independent samples are nested within a primary study. For example, the same control group is used in calculating the treatment effects or there is more than one outcome effect size. The sampling errors of the effect sizes may be correlated because the same participants are involved in calculating the effect sizes. Reported effect sizes are likely to be non-independent for various reasons. It is rare for primary studies to report only one relevant effect size. ![]() Their introduction assumes that the effect sizes are independent, which is a crucial assumption in a meta-analysis. Cheung and Vijayakumar ( 2016) recently gave a brief introduction to how neuropsychologists can conduct a meta-analysis. Many books introducing how to conduct a systematic review and meta-analysis have already been published (e.g., Borenstein, Hedges, Higgins, & Rothstein, 2009 Card, 2012 Cheung, 2015a Cooper, Hedges, & Valentine, 2009 Hedges & Olkin, 1985).
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