- Title Pages
- Dedication
- Preface
-
1 Place of Meta-analysis among Other Methods of Research Synthesis -
2 The Procedure of Meta-analysis in a Nutshell -
3 First Steps in Beginning a Meta-analysis -
4 Gathering Data: Searching Literature and Selection Criteria -
5 Extraction and Critical Appraisal of Data -
6 Effect Sizes: Conventional Choices and Calculations -
7 Using Other Metrics of Effect Size in Meta-analysis -
8 Statistical Models and Approaches to Inference -
9 Moment and Least-Squares Based Approaches to Meta-analytic Inference -
10 Maximum Likelihood Approaches to Meta-analysis -
11 Bayesian Meta-analysis -
12 Software for Statistical Meta-analysis -
13 Recovering Missing or Partial Data from Studies: A Survey of Conversions and Imputations for Meta-analysis -
14 Publication and Related Biases -
15 Temporal Trends in Effect Sizes: Causes, Detection, and Implications -
16 Statistical Models for the Meta-analysis of Nonindependent Data -
17 Phylogenetic Nonindependence and Meta-analysis -
18 Meta-analysis of Primary Data -
19 Meta-analysis of Results from Multisite Studies -
20 Quality Standards for Research Syntheses -
21 Graphical Presentation of Results -
22 Power Statistics for Meta-analysis: Tests for Mean Effects and Homogeneity -
23 Role of Meta-analysis in Interpreting the Scientific Literature -
24 Using Meta-analysis to Test Ecological and Evolutionary Theory -
25 History and Progress of Meta-analysis -
26 Contributions of Meta-analysis to Conservation and Management -
27 Conclusions: Past, Present, and Future of Meta-analysis in Ecology and Evolution - Glossary
- Frequently Asked Questions
- References
- List of Contributors
- Subject Index
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
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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- Title Pages
- Dedication
- Preface
-
1 Place of Meta-analysis among Other Methods of Research Synthesis -
2 The Procedure of Meta-analysis in a Nutshell -
3 First Steps in Beginning a Meta-analysis -
4 Gathering Data: Searching Literature and Selection Criteria -
5 Extraction and Critical Appraisal of Data -
6 Effect Sizes: Conventional Choices and Calculations -
7 Using Other Metrics of Effect Size in Meta-analysis -
8 Statistical Models and Approaches to Inference -
9 Moment and Least-Squares Based Approaches to Meta-analytic Inference -
10 Maximum Likelihood Approaches to Meta-analysis -
11 Bayesian Meta-analysis -
12 Software for Statistical Meta-analysis -
13 Recovering Missing or Partial Data from Studies: A Survey of Conversions and Imputations for Meta-analysis -
14 Publication and Related Biases -
15 Temporal Trends in Effect Sizes: Causes, Detection, and Implications -
16 Statistical Models for the Meta-analysis of Nonindependent Data -
17 Phylogenetic Nonindependence and Meta-analysis -
18 Meta-analysis of Primary Data -
19 Meta-analysis of Results from Multisite Studies -
20 Quality Standards for Research Syntheses -
21 Graphical Presentation of Results -
22 Power Statistics for Meta-analysis: Tests for Mean Effects and Homogeneity -
23 Role of Meta-analysis in Interpreting the Scientific Literature -
24 Using Meta-analysis to Test Ecological and Evolutionary Theory -
25 History and Progress of Meta-analysis -
26 Contributions of Meta-analysis to Conservation and Management -
27 Conclusions: Past, Present, and Future of Meta-analysis in Ecology and Evolution - Glossary
- Frequently Asked Questions
- References
- List of Contributors
- Subject Index
