Bayesian analysis of an inverse Gaussian correlated frailty modelKheiri, S., Kimber, A. and Meshkani, M. R. (2007) Bayesian analysis of an inverse Gaussian correlated frailty model. Computational Statistics & Data Analysis, 51 (11). pp. 5317-5326. ISSN 0167-9473 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1016/j.csda.2006.09.026 Abstract/SummaryIn survival analysis frailty is often used to model heterogeneity between individuals or correlation within clusters. Typically frailty is taken to be a continuous random effect, yielding a continuous mixture distribution for survival times. A Bayesian analysis of a correlated frailty model is discussed in the context of inverse Gaussian frailty. An MCMC approach is adopted and the deviance information criterion is used to compare models. As an illustration of the approach a bivariate data set of corneal graft survival times is analysed. (C) 2006 Elsevier B.V. All rights reserved.
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