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Biometrika 2006 93(2):303-313; doi:10.1093/biomet/93.2.303
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© 2006 Biometrika Trust

Linear life expectancy regression with censored data

Y. Q. Chen1 and S. Cheng2

1 Program in Biostatistics, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, U.S.A. yqchen{at}scharp.org, 2 Department of Epidemiology & Biostatistics, University of California, San Francisco, California 94143, U.S.A. scheng{at}biostat.ucsf.edu

In the statistical literature, life expectancy is usually characterised by the mean residual life function. Regression models are thus needed to study the association between the mean residual life functions and their covariates. In this paper, we consider a linear mean residual life model and develop inference procedures in the presence of potential censoring. The new model and inference procedures are applied to the Stanford heart transplant data. Semiparametric efficiency calculations and information bounds are also considered.

Key Words: Additive model; Counting process; Estimating equation; Mean residual life; Semiparametric model.

Received August 2004. Revised October 2005.


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