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Handbook of Meta-analysis in Ecology and Evolution$
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Julia Koricheva, Jessica Gurevitch, and Kerrie Mengersen

Print publication date: 2013

Print ISBN-13: 9780691137285

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691137285.001.0001

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Power Statistics for Meta-analysis: Tests for Mean Effects and Homogeneity

Power Statistics for Meta-analysis: Tests for Mean Effects and Homogeneity

(p.348) 22 Power Statistics for Meta-analysis: Tests for Mean Effects and Homogeneity
Handbook of Meta-analysis in Ecology and Evolution

Marc J. Lajeunesse

Princeton University Press

The common justification for meta-analysis is the increased statistical power to detect effects over what is obtained from individual studies. For ecologists and evolutionary biologists, the statistical power of meta-analysis is important because effect sizes are usually relatively small in these fields, and experimental sample sizes are often limited for logistic reasons. Consequently, many studies lack sufficient power to detect an experimental effect should it exist. This chapter provides a brief overview of the factors that determine the statistical power of meta-analysis. It presents statistics for calculating the power of pooled effect sizes to evaluate nonzero effects and the power of within- and between-study homogeneity tests. It also surveys ways to improve the statistical power of meta-analysis, and ends with a discussion on the overall utility of power statistics for meta-analysis.

Keywords:   statistical analysis, statistical power, meta-analysis, effect sizes

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