JSM 2005 - Toronto

Abstract #302463

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 216
Type: Invited
Date/Time: Tuesday, August 9, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #302463
Title: Issues of Robustness and Model Flexibility in Bayesian Survival Analysis
Author(s): Paul Gustafson*+
Companies: University of British Columbia
Address: Department of Statistics, Vancovuer, BC, V6T 1Z2, Canada
Keywords: Bayesian analysis ; survival analysis ; model misspecification
Abstract:

The literature on Bayesian methodology for survival analysis is quite rich, in the sense of demonstrating how flexible semiparametric or nonparametric Bayesian models can be applied to survival analysis problems. What seems less developed is a good sense of conditions under which the added complexity of working with such models is likely worthwhile, versus situations where one can "get away" with simpler models, even if they are less realistic. Drawing on the literature on the impact of parametric model misspecification and the literature on diagnostic methods for Bayesian models, this paper attempts to shed light on this issue. Specific questions include: When will stochastic process models for baseline hazards and time-dependent covariate effects outperform simpler parametric approaches? How much damage can misspecification of a frailty distribution cause in multivariate survival analysis? To what extent do estimators from time-static covariate effect models have a robust interpretation if the true effects are, in fact, time-varying?

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