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Meta-analysis of correlation coefficients: A Monte Carlo comparison of fixed- and random-effects methods.

journal contribution
posted on 2023-06-07, 13:40 authored by Andy FieldAndy Field
The efficacy of the Hedges and colleagues, Rosenthal-Rubin, and Hunter-Schmidt methods for combining correlation coefficients was tested for cases in which population effect sizes were both fixed and variable. After a brief tutorial on these meta-analytic methods, the author presents 2 Monte Carlo simulations that compare these methods for cases in which the number of studies in the meta-analysis and the average sample size of studies were varied. In the fixed case the methods produced comparable estimates of the average effect size; however, the Hunter-Schmidt method failed to control the Type I error rate for the associated significance tests. In the variable case, for both the Hedges and colleagues and Hunter-Schmidt methods, Type I error rates were not controlled for meta-analyses including 15 or fewer studies and the probability of detecting small effects was less than .3. Some practical recommendations are made about the use of meta-analysis.

History

Publication status

  • Published

Journal

Psychological Methods

ISSN

1082-989X

Publisher

American Psychological Association

Issue

2

Volume

6

Page range

161-180

Department affiliated with

  • Psychology Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2007-01-29

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