Fixed Effects and Variance Components Estimation in Three-Level Meta-Analysis

Spyros Konstantopoulos ()
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Spyros Konstantopoulos: Michigan State University

No 5678, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Meta-analytic methods have been widely applied to education, medicine, and the social sciences. Much of meta-analytic data are hierarchically structured since 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- and three-level meta-analysis that takes into account random variation at the second and at the 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.

Keywords: meta-analysis; multilevel models; random effects (search for similar items in EconPapers)
JEL-codes: C00 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2011-04
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (34)

Published - published in: Research Synthesis Methods, 2011, 2 (1), 61- 76

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