‘Arm‐based’ parameterization for network meta‐analysis

JOURNAL

Research Synthesis Methods

ISSN: 1759-2879

eISSN: 1759-2887

ARTICLE

‘Arm‐based’ parameterization for network meta‐analysis

Neil Hawkins, David A. Scott, Beth Woods

format_quote CITE

https://doi.org/10.1002/jrsm.1187

Volume: 7

Issue: 3

Pages: 306 - 313

Received: 9 June 2014

Accepted: 19 September 2015

Published: 19 September 2016

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. © 2015 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

JOURNAL

Research Synthesis Methods

ARTICLE

‘Arm‐based’ parameterization for network meta‐analysis

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