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

Abstract Details

Abstract - #308856
Title: WITHDRAWN: Conditional Likelihoods in Sequential Bayesian Decision Problems for Correlated Survival Data
Author(s): Daniel Garrett Polhamus
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Keywords: decision-theory ; sequential ; Bayes ; survival ; frailty
Abstract:

The computational and analytical burden of the Bayesian sequential decision problem has limited its use in efficient experimental design. However, advances in decision-theoretic loss approximation present an option for simpler, low-dimensional designs based upon optimization of the decision boundaries or a discretization of the parameter space. An alternative to sampling from the complete data likelihood for MC integration is to, instead, sample from the conditional data likelihood implicit in sequential analysis. Deriving conditional distributions for an observation given its known status can improve the efficiency of the MC integration. In this presentation, we demonstrate the utility and efficiency of these methods in the context of sequential analysis for correlated survival data through a frailty model.


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