This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 461
Type: Topic Contributed
Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #308845
Title: Semiparametric Bayesian Modeling of Spatio-Survival Data Under Cure Fraction
Author(s): Sandra Milena Hurtado Rua*+ and Dipak K. Dey
Companies: University of Connecticut and University of Connecticut
Address: Department of Statistics, Storrs, CT, 06269,
Keywords: Bayesian hierarchical models ; cure rate models ; frailty models ; Joint-Point survival models ; semiparametric baseline hazard ; spatial association
Abstract:

We propose the use of Bayesian spatial modeling with cure rates to model survival times. Recently, spatial variability, cure possibilities, and the changes over time of the survival curve have been of interest to researches. There has been research addressing each of these factors independently, but there is a need for a richer class of models to enable a comprehensive analysis of time to event data. We propose a flexible family of semiparametric baseline hazard functions with a grid defined by join-points similar to the ones used in join-point models. The hazard model is set up under the proportional hazard framework. We integrate the spatial correlation structure and the cure rates into the model. Finally, we compare performance across a broad collection of high-dimensional hierarchical models and obtain the posterior estimates, smoothed level maps of spatial frailties and cure rate


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