Abstract #301137

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2002 Program page
JSM 2002 Abstract #301137
Activity Number: 252
Type: Contributed
Date/Time: Tuesday, August 13, 2002 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Stat. Sciences*
Abstract - #301137
Title: Bayesian Analysis of a Survival Model
Author(s): Subhashis Ghosal*+ and Sujit Ghosh
Affiliation(s): North Carolina State University and North Carolina State University
Address: 220 Patterson Hall, Box 8203, 2501 Founders Drive, Raleigh, North Carolina, 27695, U.S.A.
Keywords: survival analyis ; covariate ; censoring ; Dirichlet process ; mixture ; consistency
Abstract:

We consider a mixture of exponentials as a model for survival distribution in presence of a vector of covariates. Conditionally, on the value of a parameter $\lambda$, survival distributions are assumed to be independent exponential with parameters $\lambda\exp(-z_i'\beta)$. The unknown parameter $\lambda$ is assumed to follow a distribution $H$, which is completely unknown. Observations are assumed to be randomly right-censored. This model has an interesting property that the mean lifetime of observations, rather than the hazard rates, are directly related to the covariates. We do a Bayesian semiparametric analysis of the model by putting a Dirichlet prior on $H$. The posterior can be easily computed by MCMC algorithms. The resulting posterior is consistent under certain conditions.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2002 program

JSM 2002

For information, contact meetings@amstat.org or phone (703) 684-1221.

If you have questions about the Continuing Education program, please contact the Education Department.

Revised March 2002