A noncentral t regression model for meta-analysis

Gregory Camilli, Jimmy de la Torrede, Chia Yi Chiu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)125-153
Number of pages29
JournalJournal of Educational and Behavioral Statistics
Volume35
Issue number2
DOIs
StatePublished - Jun 2010

All Science Journal Classification (ASJC) codes

  • Education
  • Social Sciences (miscellaneous)

Keywords

  • MCMC estimation
  • Meta-analysis
  • Multilevel analysis
  • Noncentral t distribution
  • Psychotherapy outcomes

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