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Efficient estimation for the Cox model with varying coefficients

Author

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  • Kani Chen
  • Huazhen Lin
  • Yong Zhou

Abstract

A proportional hazards model with varying coefficients allows one to examine the extent to which covariates interact nonlinearly with an exposure variable. A global partial likelihood method, in contrast with the local partial likelihood method of Fan et al. (2006), is proposed for estimation of varying coefficient functions. The proposed estimators are proved to be consistent and asymptotically normal. Semiparametric efficiency of the estimators is demonstrated in terms of their linear functionals. Evidence in support of the superiority of the method is presented in numerical studies and real examples. Copyright 2012, Oxford University Press.

Suggested Citation

  • Kani Chen & Huazhen Lin & Yong Zhou, 2012. "Efficient estimation for the Cox model with varying coefficients," Biometrika, Biometrika Trust, vol. 99(2), pages 379-392.
    • Handle: RePEc:oup:biomet:v:99:y:2012:i:2:p:379-392
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    File URL: http://hdl.handle.net/10.1093/biomet/asr081
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    Cited by:

    1. Huazhen Lin & Zhe Fei & Yi Li, 2016. "A Semiparametrically Efficient Estimator of the Time-Varying Effects for Survival Data with Time-Dependent Treatment," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 649-663, September.
    2. Huazhen Lin & Hyokyoung G. Hong & Baoying Yang & Wei Liu & Yong Zhang & Gang-Zhi Fan & Yi Li, 2019. "Nonparametric Time-Varying Coefficient Models for Panel Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 548-566, December.
    3. X. Joan Hu & Rhonda J. Rosychuk, 2016. "Marginal regression analysis of recurrent events with coarsened censoring times," Biometrics, The International Biometric Society, vol. 72(4), pages 1113-1122, December.
    4. Qu, Lianqiang & Song, Xinyuan & Sun, Liuquan, 2018. "Identification of local sparsity and variable selection for varying coefficient additive hazards models," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 119-135.

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