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Meta-regression with partial information on summary trial or patient characteristics

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Hemming, Karla, Hutton, Jane L., Maguire, M. J. and Marson, A. G.. (2010) Meta-regression with partial information on summary trial or patient characteristics. Statistics in Medicine, Vol.29 (No.12). pp. 1312-1324. ISSN 0277-6715

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Official URL: http://dx.doi.org/10.1002/sim.3848

Abstract

We present a model for meta-regression in the presence of missing information on some of the study level covariates, obtaining inferences using Bayesian methods. In practice, when confronted with missing covariate data in a meta-regression, it is common to carry out a complete case or available case analysis. We propose to use the full observed data, modelling the joint density as a factorization of a meta-regression model and a conditional factorization of the density for the covariates. With the inclusion of several covariates, inter-relations between these covariates are modelled. Under this joint likelihood-based approach, it is shown that the lesser assumption of the covariates being Missing At Random is imposed, instead of the more usual Missing Completely At Random (MCAR) assumption. The model is easily programmable in WinBUGS, and we examine, through the analysis of two real data sets, sensitivity and robustness of results to the MCAR assumption. Copyright (C) 2010 John Wiley & Sons, Ltd.

Item Type: Journal Article
Subjects: Q Science > QH Natural history > QH301 Biology
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
R Medicine
Q Science > QA Mathematics
Divisions: Faculty of Science > Statistics
Journal or Publication Title: Statistics in Medicine
Publisher: John Wiley & Sons Ltd.
ISSN: 0277-6715
Date: 30 May 2010
Volume: Vol.29
Number: No.12
Number of Pages: 13
Page Range: pp. 1312-1324
Identification Number: 10.1002/sim.3848
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Medical Research, National Institute for Health Research (NIHR)
Grant number: G0400642
URI: http://wrap.warwick.ac.uk/id/eprint/5742

Data sourced from Thomson Reuters' Web of Knowledge

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