Bayesian Transformation Models for Multivariate Survival Data |
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Authors: | Mário de Castro Ming‐Hui Chen Joseph G Ibrahim John P Klein |
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Institution: | 1. Instituto de Ciências Matemáticas e de Computa??o, Universidade de S?o Paulo;2. Department of Statistics, University of Connecticut;3. Department of Biostatistics, University of North Carolina;4. Division of Biostatistics, Medical College of Wisconsin |
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Abstract: | In this paper, we propose a general class of Gamma frailty transformation models for multivariate survival data. The transformation class includes the commonly used proportional hazards and proportional odds models. The proposed class also includes a family of cure rate models. Under an improper prior for the parameters, we establish propriety of the posterior distribution. A novel Gibbs sampling algorithm is developed for sampling from the observed data posterior distribution. A simulation study is conducted to examine the properties of the proposed methodology. An application to a data set from a cord blood transplantation study is also reported. |
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Keywords: | cure rate Gamma frailty Gibbs sampler piecewise exponential model proportional hazards model proportional odds model |
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