Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48759
Title: Objective bayesian meta-analysis for sparse discrete data
Authors: Moreno, E.
Vázquez-Polo, F. J. 
Negrín, M. A. 
Keywords: Random Effects Models
Selection
Distributions
Impact
Risk
Issue Date: 2014
Publisher: 0277-6715
Journal: Statistics in Medicine 
Abstract: This paper presents a Bayesian model for meta-analysis of sparse discrete binomial data, which are out of the scope of the usual hierarchical normal random-effect models. Treatment effectiveness data are often of this type. The crucial linking distribution between the effectiveness conditional on the healthcare center and the unconditional effectiveness is constructed from specific bivariate classes of distributions with given marginals. This assures coherency between the marginal and conditional prior distributions utilized in the analysis. Further, we impose a bivariate class of priors that is able to accommodate a wide range of heterogeneity degrees between the multicenter clinical trials involved. Applications to real multicenter data are given and compared with previous meta-analysis. Copyright (c) 2014 John Wiley & Sons, Ltd.
URI: http://hdl.handle.net/10553/48759
ISSN: 0277-6715
DOI: 10.1002/sim.6163
Source: Statistics in Medicine[ISSN 0277-6715],v. 33, p. 3676-3692
Appears in Collections:Artículos
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