title: Updating meta-analytic research findings: Bayesian approaches versus the medical model.
abstract: The authors examine 3 methods of combining new studies into existing meta-analyses: (a) adding the new study or studies to the database and recalculating the meta-analysis (the medical model); (b) using the Bayesian procedure advocated by F. L. Schmidt and J. E. Hunter (1977) and F. L. Schmidt, J. E. Hunter, K. Pearlman, and G. S. Shane (1979) to update the meta-analysis; and (c) using the Bayesian methods advocated by these authors and M. T. Brannick (2001) and M. T. Brannick, S. M. Hall, and Y. Liu (2002) to estimate study-specific parameters. Method b was found to severely overweight new studies relative to the previous studies contained in the meta-analysis, and Method c was found to do the same while also requiring an assumption with a low prior probability of being correct, causing the method to violate Bayesian principles. The authors present an alternative Bayesian procedure that does not suffer from these drawbacks and yields meta-analytic results very similar to those obtained with the medical model. They recommend use of the medical model or this alternative Bayesian procedure.
authors: Department of Management and Organizations, Henry B. Tippie College of Business, University of Iowa, Iowa City, IA 52242, USA. frank-schmidt@uiowa.edu
authors: Frank L
authors: FL
authors: Schmidt
authors: Nambury S
authors: NS
authors: Raju
mesh_terms: D001499:Bayes Theorem; D035843:Biomedical Research / Q000592:standards* / Q000706:statistics & numerical data*; D006801:Humans; D015201:Meta-Analysis as Topic; D008954:Models, Biological; D011584:Psychology / Q000379:methods* / Q000706:statistics & numerical data*