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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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Statistical Models for the Meta-analysis of Nonindependent Data

Statistical Models for the Meta-analysis of Nonindependent Data

Chapter:
(p.255) 16 Statistical Models for the Meta-analysis of Nonindependent Data
Source:
Handbook of Meta-analysis in Ecology and Evolution
Author(s):

Kerrie Mengersen

Michael D. Jennions

Christopher H. Schmid

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691137285.003.0016

In many meta-analyses, independence is questionable because there are several effect estimates per study and/or some of the individual studies included in the meta-analysis might not provide independent estimates of the effect. Within-study nonindependence can arise due to multiple measures of the same effect on the same experimental units being made over time, multiple treatments being compared to the same set of control individuals, or different measures being taken (e.g., plant height, dry weight, and photosynthesis rate) from the same experimental units to generate several different effect size estimates. This chapter discusses nonindependence among effect sizes both within and among studies. It focuses on four commonplace situations where nonindependence can occur in ecology and evolution meta-analyses. Each of these four situations is illustrated with a single case study.

Keywords:   non-independence, meta-analysis, effect sizes, ecology, evolution

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