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Accounting for heterogeneity in meta-analysis using a multiplicative model-an empirical study

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journal contribution
posted on 04.10.2016, 15:08 by David Mawdsley, Julian P. T. Higgins, Alex J. Sutton, Keith R. Abrams
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.

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Citation

Research Synthesis Methods, 2016, DOI: 10.1002/jrsm.1216

Author affiliation

/Organisation/COLLEGE OF MEDICINE, BIOLOGICAL SCIENCES AND PSYCHOLOGY/School of Medicine/Department of Health Sciences

Version

AM (Accepted Manuscript)

Published in

Research Synthesis Methods

Publisher

Wiley for Society for Research Synthesis Methodology

issn

1759-2879

eissn

1759-2887

Acceptance date

09/05/2016

Copyright date

2016

Available date

03/06/2017

Publisher version

http://onlinelibrary.wiley.com/doi/10.1002/jrsm.1216/abstract;jsessionid=6113DE9CFE35871800EBFF34372A51E6.f04t02

Notes

Following the embargo period the above license applies.

Language

en

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