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Title: Accounting for heterogeneity in meta-analysis using a multiplicative model-an empirical study
Authors: Mawdsley, David
Higgins, Julian P. T.
Sutton, Alex J.
Abrams, Keith R.
First Published: 3-Jun-2016
Publisher: Wiley for Society for Research Synthesis Methodology
Citation: Research Synthesis Methods, 2016, DOI: 10.1002/jrsm.1216
Abstract: In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In this paper, we compare the two models using a random sample of 448 meta-analyses drawn from the Cochrane Database of Systematic Reviews. In general, differences in goodness of fit are modest. The multiplicative model tends to give results that are closer to the null, with a narrower confidence interval. Both approaches make different assumptions about the outcome of the meta-analysis. In our opinion, the selection of the more appropriate model will often be guided by whether the multiplicative model's assumption of a single effect size is plausible. Copyright © 2016 John Wiley & Sons, Ltd.
DOI Link: 10.1002/jrsm.1216
ISSN: 1759-2879
eISSN: 1759-2887
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016 John Wiley & Sons, Ltd. This version of this article is distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License ( ), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Description: Following the embargo period the above license applies.
Appears in Collections:Published Articles, Dept. of Health Sciences

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