Advances in Meta-Analysis pp 55-66 | Cite as

# Power for the Test of Homogeneity in Fixed and Random Effects Models

Chapter

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## Abstract

This chapter will illustrate methods for the power of the test of homogeneity in fixed and random effects models. In fixed effects models, the test of homogeneity provides evidence about whether the effect sizes in a meta-analysis are measuring a common effect size. The test of homogeneity in random effects models is a test of the statistical significance of the variance component, the between-studies variance. The chapter gives examples of how to compute the power for the test of homogeneity in both fixed and random effects models.

## Keywords

Variance Component Average Difference Random Effect Model Homogeneity Test Effect Size Estimate
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

## References

- Hedges, L.V., and T.D. Pigott. 2001. Power analysis in meta-analysis.
*Psychological Methods*6: 203–217.CrossRefGoogle Scholar - Hedges, L.V., and J.L. Vevea. 1998. Fixed- and random-effects models in meta-analysis.
*Psychological Methods*3(4): 486–504.CrossRefGoogle Scholar - Higgins, J.P.T., and S.G. Thompson. 2002. Quantifying heterogeneity in a meta-analysis.
*Statistics in Medicine*21: 1539–1558.CrossRefGoogle Scholar - Satterthwaite, F.E. 1946. An approximate distribution of estimates of variance components.
*Biometrics Bulletin*2: 110–114.CrossRefGoogle Scholar

## Copyright information

© Springer Science+Business Media, LLC 2012