Jump to ContentJump to Main Navigation
Handbook of Meta-analysis in Ecology and Evolution$
Users without a subscription are not able to see the full content.

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

Show Summary Details
Page of

PRINTED FROM PRINCETON SCHOLARSHIP ONLINE (www.princeton.universitypressscholarship.com). (c) Copyright Princeton University Press, 2017. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a monograph in HSO for personal use (for details see http://www.universitypressscholarship.com/page/privacy-policy).date: 16 December 2017

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

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

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

Marc J. Lajeunesse

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691137285.003.0022

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

Princeton Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us.