A Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons

Author:

Hong Hwanhee1,Chu Haitao2,Zhang Jing3,Carlin Bradley P.2

Affiliation:

1. Department of Mental Health; Johns Hopkins University; Baltimore MD 21205 USA

2. Division of Biostatistics; University of Minnesota; Minneapolis MN 55405 USA

3. Department of Epidemiology and Biostatistics; University of Maryland, College Park; MD 20742 USA

Funder

NIAID

NIDCR

NCI

NIMHD

US NCI

Publisher

Wiley

Subject

Education

Reference53 articles.

1. Extending methods for investigating the relationship between treatment effect and baseline risk from pairwise meta-analysis to network meta-analysis;Achana;Statistics in Medicine,2013

2. Ades AE Caldwell DM Reken S Welton NJ Sutton AJ Dias S 2012 NICE DSU Technical Support Document 7: evidence synthesis of treatment efficacy in decision making: a reviewers checklist http://www.nicedsu.org.uk

3. Modeling covariance matrices in terms of standard deviations and correlations, with application to shrinkage;Barnard;Statistica Sinica,2000

4. Multivariate meta-analysis of mixed outcomes: a Bayesian approach;Bujkiewicz;Statistics in Medicine,2013

5. Simultaneous comparison of multiple treatments: combining direct and indirect evidence;Caldwell;BMJ,2005

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