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A Noncentral t Regression Model for Meta-Analysis

Author

Listed:
  • Gregory Camilli

    (University of Colorado at Boulder)

  • Jimmy de la Torre
  • Chia-Yi Chiu

    (Rutgers, The State University of New Jersey)

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.

Suggested Citation

  • Gregory Camilli & Jimmy de la Torre & Chia-Yi Chiu, 2010. "A Noncentral t Regression Model for Meta-Analysis," Journal of Educational and Behavioral Statistics, , vol. 35(2), pages 125-153, April.
    • Handle: RePEc:sae:jedbes:v:35:y:2010:i:2:p:125-153
    DOI: 10.3102/1076998609346966
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    References listed on IDEAS

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    1. Bayarri M.J. & Mayoral A.M., 2002. "Bayesian Design of," The American Statistician, American Statistical Association, vol. 56, pages 207-214, August.
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