Two new methods to fit models for network meta-analysis with random inconsistency effects

Two new methods to fit models for network meta-analysis with random inconsistency effects

Abstract Background Meta-analysis is a valuable tool for combining evidence from multiple studies. Network meta-analysis is becoming more widely used as a means to compare multiple treatments in the same analysis. However, a network meta-analysis may exhibit inconsistency, whereby the treatment effe...

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Bibliographic Details
Main Authors: Martin Law, Dan Jackson, Rebecca Turner, Kirsty Rhodes, Wolfgang Viechtbauer
Format: Article
Language:English
Published: BMC 2016-07-01
Series:BMC Medical Research Methodology
Subjects:
Network meta-analysis
Importance sampling
Random inconsistency effects
Informative priors
Online Access:http://link.springer.com/article/10.1186/s12874-016-0184-5

Internet

http://link.springer.com/article/10.1186/s12874-016-0184-5

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