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Semiparametric Regression Analysis of Mean Residual Life with Censored Survival Data

Author

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  • Ying Chen

    (Division of Biostatistics, School of Public Health, University of California, Berkeley)

  • Su-Chun Cheng

    (Department of Epidemiology & Biostatistics, University of California, San Francisco)

Abstract

As a function of time t, mean residual life is the remaining life expectancy of a subject given survival up to t. The proportional mean residual life model, proposed by Oakes & Dasu (1990), provides an alternative to the Cox proportional hazards model to study the association between survival times and covariates. In the presence of censoring, we develop semiparametric inference procedures for the regression coefficients of the Oakes-Dasu model using martingale theory for counting processes. We also present simulation studies and an application to the Veterans' Administration lung cancer data.

Suggested Citation

  • Ying Chen & Su-Chun Cheng, 2004. "Semiparametric Regression Analysis of Mean Residual Life with Censored Survival Data," U.C. Berkeley Division of Biostatistics Working Paper Series 1146, Berkeley Electronic Press.
    • Handle: RePEc:bep:ucbbio:1146
    Note: oai:bepress.com:ucbbiostat-1146
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    References listed on IDEAS

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    1. A. N. Pettitt, 1984. "Proportional Odds Models for Survival Data and Estimates Using Ranks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(2), pages 169-175, June.
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    Cited by:

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