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Biometrika 1988 75(4):693-704; doi:10.1093/biomet/75.4.693
© 1988 by Biometrika Trust
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Modelling accelerated failure time with a Dirichlet process

RONALD CHRISTENSEN and WESLEY JOHNSON

Department of Mathematical Sciences, Montana State University Bozeman, Montana 59717, U.S.A.
Division of Statistics, University of California Davis, California 95616, U.S.A.

The relationship between survival times and covariates is modelled via the accelerated failure time model with a Dirichlet process prior assumed for the underlying baseline survival function. Emphasis is placed on estimating the survival distribution for future individuals with given covariates. A method of estimating regression coefficients which uses the marginal distribution for observed censored data is given. The proposed procedures are shown to perform reasonably on two artificial data sets, and an analysis of the Stanford heart transplant data is given.

Key Words: Accelerated failure time • Dirichlet process • Empirical Bayes • Nonparametric Bayes • Semiparametric model • Stanford heart transplant data


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