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. Copyright 2006, Oxford University Press.
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Article provided by Oxford University Press for Biometrika Trust in its journal Biometrika.
Volume (Year): 93 (2006) Issue (Month): 2 (June) Pages: 303-313 Download reference. The following formats are available: HTML
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