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

Abstract Details

Activity Number: 390
Type: Topic Contributed
Date/Time: Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #307853
Title: Nonparametric Mixture Regression for Survival Data
Author(s): Matthew Taddy*+
Companies: Chicago Booth
Address: , , ,
Keywords: survival analysis ; dirichlet process ; mixture model ; regression

We seek to develop a uni?ed fully nonparametric framework (uni?ed in that all functionals of interest are available through a single inferential process for response densities) for multivariate survival data in the presence of a regression component. We obtain inference for survival and hazard functions based on the conditional distribution for survival responses given covariates implied by a joint distribution mixture model. In addition, we present a general framework for applying our mixture models in treatment-control settings through use of two correlated random mixing distributions.

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