Multivariate survival analysis with positive stable frailties.
In this paper, we describe Bayesian modeling of dependent multivariate survival data using positive stable frailty distributions. A flexible baseline hazard formulation using a piecewise exponential model with a correlated prior process is used. The estimation of the stable law parameter together with the parameters of the (conditional) proportional hazards model is facilitated by a modified Gibbs sampling procedure. The methodology is illustrated on kidney infection data (McGilchrist and Aisbett, 1991).
Qiou
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Palisades Research, Inc. Morganville, New Jersey 07751, USA.
Ravishanker
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Dey
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DK
D000465:Algorithms; D001499:Bayes Theorem; D001699:Biometry; D005260:Female; D006801:Humans; D007674:Kidney Diseases / Q000209:etiology; D008297:Male; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D016019:Survival Analysis