Volume 3, Issue 2
Special Issue Paper

Using network meta‐analysis to evaluate the existence of small‐study effects in a network of interventions

Anna Chaimani

Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece

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Georgia Salanti

Corresponding Author

E-mail address: gsalanti@cc.uoi.gr

+30 26510 07757

Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece

Georgia Salanti, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, Ioannina 45110 Greece.

E‐mail: Georgia Salanti gsalanti@cc.uoi.gr

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First published: 01 June 2012
Citations: 109

This article is published in Research Synthesis Methods as a special issue on Network Meta‐analysis, edited by Georgia Salanti, University of Ioannina, Greece.

Abstract

Suggested methods for exploring the presence of small‐study effects in a meta‐analysis and the possibility of publication bias are associated with important limitations. When a meta‐analysis comprises only a few studies, funnel plots are difficult to interpret, and regression‐based approaches to test and account for small‐study effects have low power. Assuming that the cause of funnel plot asymmetry is likely to affect an entire research field rather than only a particular comparison of interventions, we suggest that network meta‐regression is employed to account for small‐study effects in a set of related meta‐analyses. We present several possible models for the direction and distribution of small‐study effects and we describe the methods by re‐analysing two published networks. Copyright © 2012 John Wiley & Sons, Ltd.

Number of times cited according to CrossRef: 109

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