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Res Synth Methods. 2012 Jun;3(2):161-76. doi: 10.1002/jrsm.57. Epub 2012 Jun 1.

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

Author information

1
Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
2
Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece. 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.

KEYWORDS:

funnel plot; optimism bias; publication bias; selective reporting bias; sponsorship bias

PMID:
26062088
DOI:
10.1002/jrsm.57

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