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Biometrika 2006 93(2):329-342; doi:10.1093/biomet/93.2.329
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© 2006 Biometrika Trust

On the accelerated failure time model for current status and interval censored data

Lu Tian1 and Tianxi Cai2

1 Department of Preventive Medicine, Northwestern University, 680 N. Lake Shore Drive, Suite 1102, Chicago, Illinois 60611, U.S.A. lutian{at}northwestern.edu, 2 Department of Biostatistics, Harvard University, 655 Huntington Avenue, Boston, Massachusetts 02115, U.S.A. tcai{at}hsph.harvard.edu

This paper introduces a novel approach to making inference about the regression parameters in the accelerated failure time model for current status and interval censored data. The estimator is constructed by inverting a Wald-type test for testing a null proportional hazards model. A numerically efficient Markov chain Monte Carlo based resampling method is proposed for obtaining simultaneously the point estimator and a consistent estimator of its variance-covariance matrix. We illustrate our approach with interval censored datasets from two clinical studies. Extensive numerical studies are conducted to evaluate the finite-sample performance of the new estimators.

Key Words: Accelerated failure time model; Current status data; Interval censoring; Markov chain Monte Carlo; Nonparametric maximum likelihood estimator.

Received September 2004. Revised October 2005.


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