Abstract #301450

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JSM 2003 Abstract #301450
Activity Number: 205
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Stat. Sciences
Abstract - #301450
Title: A Beta Stacy Process for Nonparametric Survival Analysis
Author(s): Fabio Rigat*+
Companies: Duke University
Address: 4416 A American Dr., Durham, NC, 27705,
Keywords: Bayesian nonparametric survival analysis ; proportional hazards model ; Dirichlet process ; Beta Stacy process ; Levy processes
Abstract:

We propose a semiparametric proportional hazards survival model by adopting the Beta Stacy process introduced by Walker and Muliere (1997) as the baseline cumulative distribution function. The process is conjugate with respect to the likelihood arising from right censored data. Furthermore being neutral to the right (Doksum 1974), the Beta Stacy is a one to one transformation of a Levy process. The posterior baseline can thus be simulated by the inverse Levy measure algorithm by Wolpert and Ickstadt (1998), whereas the regression parameters are sampled through a Metropolis-Hastings scheme. Numerical results are given for a dataset of breast cancer survival times including clinical and genetic covariates.

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