title: Multivariate survival analysis with positive stable frailties.
abstract: 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).
authors.affiliation: Palisades Research, Inc. Morganville, New Jersey 07751, USA.
authors.forename: Z
authors.initials: Z
authors.lastname: Qiou
authors.forename: N
authors.initials: N
authors.lastname: Ravishanker
authors.forename: D K
authors.initials: DK
authors.lastname: Dey
mesh_terms: 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