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

Authors


  • This article is published in Research Synthesis Methods as a special issue on Network Meta-analysis, edited by Georgia Salanti, University of 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

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.

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