Abstract #300887

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JSM 2003 Abstract #300887
Activity Number: 148
Type: Invited
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract - #300887
Title: Bayesian Methods and Cure Rate Survival Analysis
Author(s): Debajyoti Sinha*+
Companies: Medical University of South Carolina
Address: 135 Canon St., Suite 303, Charleston, SC, 29425-0835,
Keywords: mixture model ; exponentiated model ; prior distribution ; MCMC ; K-L distance
Abstract:

We discuss Bayesian methods for right censored survival data for populations with a surviving (cure) fraction. We compare different classes of cure rate survival models in the context of Bayesian analysis. We investigate the properties of the posteriors, methods of prior elicitation, methods of model diagnostics and model selection, and associated Bayesian computational tools under these different classes of models. By introducing latent variables, we develop efficient Markov chain Monte Carlo algorithms for sampling from the posterior distribution of the parameters of these models. Our results are illustrated via Bayesian analysis of some real data sets from cancer studies and clinical trials.

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