Literature DB >> 17371079

Updating meta-analytic research findings: Bayesian approaches versus the medical model.

Frank L Schmidt1, Nambury S Raju.   

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. (c) 2007 APA, all rights reserved.

Mesh:

Year:  2007        PMID: 17371079     DOI: 10.1037/0021-9010.92.2.297

Source DB:  PubMed          Journal:  J Appl Psychol        ISSN: 0021-9010


  1 in total

1.  Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach.

Authors:  Mike W-L Cheung; Suzanne Jak
Journal:  Front Psychol       Date:  2016-05-23
  1 in total

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