Linear Life Expectancy Regression with Censored Data

Ying Chen and Su-Chun Cheng
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Ying Chen: Division of Biostatistics, School of Public Health, University of California, Berkeley
Su-Chun Cheng: Department of Epidemiology and Biostatistics, University of California, San Francisco

No 1154, U.C. Berkeley Division of Biostatistics Working Paper Series from Berkeley Electronic Press

Abstract: Life expectancy, i.e., mean residual life function, has been of important practical and scientific interests to characterise the distribution of residual life. Regression models are often needed to model the association between life expectancy and its covariates. In this article, we consider a linear mean residual life model and further developed some inference procedures in presence of censoring. The new model and proposed inference procedure will be demonstrated by numerical examples and application to the well-known Stanford heart transplant data. Additional semiparametric efficiency calculation and information bound are also considered.

Keywords: Counting process; Estimating equation; Mean residual life function; Additive model; Semiparametric model (search for similar items in EconPapers)
Date: 2004-08-02
Note: oai:bepress.com:ucbbiostat-1154
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