A Noncentral t Regression Model for Meta-Analysis

Gregory Camilli, Jimmy de la Torre and Chia-Yi Chiu
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Gregory Camilli: University of Colorado at Boulder
Chia-Yi Chiu: Rutgers, The State University of New Jersey

Journal of Educational and Behavioral Statistics, 2010, vol. 35, issue 2, 125-153

Abstract: In this article, three multilevel models for meta-analysis are examined. Hedges and Olkin suggested that effect sizes follow a noncentral t distribution and proposed several approximate methods. Raudenbush and Bryk further refined this model; however, this procedure is based on a normal approximation. In the current research literature, this approximate procedure has not been compared to one based directly on the noncentral t distribution, which is the approach taken in this article. A multilevel model is presented, and estimation is carried out on a real data set using the Markov chain Monte Carlo (MCMC) procedure. A simulation study is then conducted to examine the properties of the noncentral t approach in more depth. Finally, an example of code written in WinBUGS is given, which may be useful to researchers across a broad range of disciplines.

Keywords: meta-analysis; multilevel analysis; noncentral t distribution; MCMC estimation; psychotherapy outcomes (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:35:y:2010:i:2:p:125-153

DOI: 10.3102/1076998609346966

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