Empirical Benchmarks for Interpreting Effect Size Variability in Meta-Analysis
Empirical Benchmarks for Interpreting Effect Size Variability in Meta-Analysis
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New York, USA: Cambridge University Press
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English
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Publisher
New York, USA: Cambridge University Press
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Generalization in meta-analyses is not a dichotomous decision (typically encountered in papers using the Q test for homogeneity, the 75% rule, or null hypothesis tests). Inattention to effect size variability in meta-analyses may stem from a lack of guidelines for interpreting credibility intervals. In this commentary, we describe two methods for m...
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Empirical Benchmarks for Interpreting Effect Size Variability in Meta-Analysis
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TN_cdi_proquest_journals_1933611985
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_1933611985
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ISSN
1754-9426
E-ISSN
1754-9434
DOI
10.1017/iop.2017.44
