Fixed effects and variance components estimation in three-level meta-analysis
Article first published online: 10 JUN 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Research Synthesis Methods
Volume 2, Issue 1, pages 61–76, March 2011
How to Cite
Konstantopoulos, S. (2011), Fixed effects and variance components estimation in three-level meta-analysis. Res. Synth. Method, 2: 61–76. doi: 10.1002/jrsm.35
- Issue published online: 27 JUN 2011
- Article first published online: 10 JUN 2011
- Manuscript Accepted: 26 APR 2011
- Manuscript Revised: 18 APR 2011
- Manuscript Received: 29 APR 2010
- multilevel models;
- variance components;
- effect sizes
Meta-analytic methods have been widely applied to education, medicine, and the social sciences. Much of meta-analytic data are hierarchically structured because effect size estimates are nested within studies, and in turn, studies can be nested within level-3 units such as laboratories or investigators, and so forth. Thus, multilevel models are a natural framework for analyzing meta-analytic data. This paper discusses the application of a Fisher scoring method in two-level and three-level meta-analysis that takes into account random variation at the second and third levels. The usefulness of the model is demonstrated using data that provide information about school calendar types. sas proc mixed and hlm can be used to compute the estimates of fixed effects and variance components. Copyright © 2011 John Wiley & Sons, Ltd.