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Multivariate Survival Analysis with Positive Stable Frailties
Author(s) -
Qiou Zuqiang,
Ravishanker Nalini,
Dey Dipak K.
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00637.x
Subject(s) - multivariate statistics , gibbs sampling , statistics , proportional hazards model , mathematics , multivariate analysis , bayesian probability , piecewise , econometrics , mathematical analysis
Summary. 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).