Bayesian Analysis

Modeling censored lifetime data using a mixture of gammas baseline

Timothy E. Hanson

Full-text: Open access

Abstract

We propose a Bayesian semiparametric accelerated failure time (AFT) model in which the baseline survival distribution is modeled as a Dirichlet process mixture of gamma densities. The model is highly flexible and readily captures features such as multimodality in predictive survival densities. The approach can be used in a "black-box" manner in that the prior information needed to fit the model can be quite vague, and we recommend a particular prior in the absence of information on the baseline survival distribution. The resulting posterior baseline distribution has mass only on the positive reals, a desirable feature in a failure-time model. The formulae needed to fit the model are available in closed-form and the model is relatively easy to code and implement. We provide both simulated and real data examples, including data on the cosmetic effects of cancer therapy.

Article information

Source
Bayesian Anal. Volume 1, Number 3 (2006), 575-594.

Dates
First available in Project Euclid: 22 June 2012

Permanent link to this document
https://projecteuclid.org/euclid.ba/1340371053

Digital Object Identifier
doi:10.1214/06-BA119

Mathematical Reviews number (MathSciNet)
MR2221289

Zentralblatt MATH identifier
1331.62389

Keywords
Accelerated failure time Dirichlet process mixture

Citation

Hanson, Timothy E. Modeling censored lifetime data using a mixture of gammas baseline. Bayesian Anal. 1 (2006), no. 3, 575--594. doi:10.1214/06-BA119. https://projecteuclid.org/euclid.ba/1340371053


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