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Continuous auxiliary covariate in additive hazards regression for survival data

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Abstract

This paper considers the additive hazards regression analysis by utilizing continuous auxiliary covariate information to improve the efficiency of the statistical inference when the primary covariate is ascertained only for a randomly selected subsample. The authors construct a martingale-based estimating equation for the regression parameter and establish the asymptotic consistency and normality of the resultant estimators. Simulation study shows that the proposed method can greatly improve the efficiency compared with the estimator which discards the auxiliary covariate information in a variety of settings. A real example is also provided as an illustration.

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Authors and Affiliations

  1. School of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, China

    Xiaoping Shi

  2. School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, China

    Xiaoping Shi, Yanyan Liu & Yuanshan Wu

Authors
  1. Xiaoping Shi
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  2. Yanyan Liu
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  3. Yuanshan Wu
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Corresponding author

Correspondence to Xiaoping Shi.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 11171263, 41261087, and the Doctoral Fund of Ministry of Education of China under Grant Nos. 20110141110004, 20110141120004.

This paper was recommended for publication by Editor SUN Liuquan.

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Shi, X., Liu, Y. & Wu, Y. Continuous auxiliary covariate in additive hazards regression for survival data. J Syst Sci Complex 27, 1247–1262 (2014). https://doi.org/10.1007/s11424-014-3010-3

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  • DOI: https://doi.org/10.1007/s11424-014-3010-3

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