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A Note on Empirical Likelihood Inference of Residual Life Regression

Author

Listed:
  • Ying Chen

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

  • Yichuan Zhao

    (Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia)

Abstract

Mean residual life function, or life expectancy, is an important function to characterize distribution of residual life. The proportional mean residual life model by Oakes and Dasu (1990) is a regression tool to study the association between life expectancy and its associated covariates. Although semiparametric inference procedures have been proposed in the literature, the accuracy of such procedures may be low when the censoring proportion is relatively large. In this paper, the semiparametric inference procedures are studied with an empirical likelihood ratio method. An empirical likelihood confidence region is constructed for the regression parameters. The proposed method is further compared with the normal approximation based method through a simulation study.

Suggested Citation

  • Ying Chen & Yichuan Zhao, 2004. "A Note on Empirical Likelihood Inference of Residual Life Regression," U.C. Berkeley Division of Biostatistics Working Paper Series 1153, Berkeley Electronic Press.
    • Handle: RePEc:bep:ucbbio:1153
    Note: oai:bepress.com:ucbbiostat-1153
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