A Bayesian Semiparametric Accelerated Failure Time Model
Article first published online: 26 MAY 2004
Volume 55, Issue 2, pages 477–483, June 1999
How to Cite
Walker, S. and Mallick, B. K. (1999), A Bayesian Semiparametric Accelerated Failure Time Model. Biometrics, 55: 477–483. doi: 10.1111/j.0006-341X.1999.00477.x
- Issue published online: 26 MAY 2004
- Article first published online: 26 MAY 2004
- Received April 1997. Revised August 1998. Accepted August 1998.
- Markov chain Monte Carlo;
- Partial exchangeability;
- Pólya trees
Summary. A Bayesian semiparametric approach is described for an accelerated failure time model. The error distribution is assigned a Polya tree prior and the regression parameters a noninformative hierarchical prior. Two cases are considered: the first assumes error terms are exchangeable; the second assumes that error terms are partially exchangeable. A Markov chain Monte Carlo algorithm is described to obtain a predictive distribution for a future observation given both uncensored and censored data.