‘Arm-based’ parameterization for network meta-analysis

Hawkins, N. , Scott, D. A. and Woods, B. (2015) ‘Arm-based’ parameterization for network meta-analysis. Research Synthesis Methods, 7(3), pp. 306-313. (doi: 10.1002/jrsm.1187) (PMID::26610409) (PMCID:PMC5063191)

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We present an alternative to the contrast‐based parameterization used in a number of publications for network meta‐analysis. This alternative “arm‐based” parameterization offers a number of advantages: it allows for a “long” normalized data structure that remains constant regardless of the number of comparators; it can be used to directly incorporate individual patient data into the analysis; the incorporation of multi‐arm trials is straightforward and avoids the need to generate a multivariate distribution describing treatment effects; there is a direct mapping between the parameterization and the analysis script in languages such as WinBUGS and finally, the arm‐based parameterization allows simple extension to treatment‐specific random treatment effect variances. We validated the parameterization using a published smoking cessation dataset. Network meta‐analysis using arm‐ and contrast‐based parameterizations produced comparable results (with means and standard deviations being within +/− 0.01) for both fixed and random effects models. We recommend that analysts consider using arm‐based parameterization when carrying out network meta‐analyses.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Hawkins, Professor Neil
Authors: Hawkins, N., Scott, D. A., and Woods, B.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
Journal Name:Research Synthesis Methods
ISSN (Online):1759-2887
Copyright Holders:Copyright © 2015 The Authors
First Published:First published in Research Synthesis Methods 7(3):306-313
Publisher Policy:Reproduced under a Creative Commons License

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