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Weighted estimating equations for additive hazards models with missing covariates

Author

Listed:
  • Lihong Qi

    (University of California Davis)

  • Xu Zhang

    (University of Texas Health Science Center at Houston
    University of Texas Health Science Center at Houston)

  • Yanqing Sun

    (University of North Carolina at Charlotte)

  • Lu Wang

    (University of California Davis)

  • Yichuan Zhao

    (Georgia State University)

Abstract

This paper presents simple weighted and fully augmented weighted estimators for the additive hazards model with missing covariates when they are missing at random. The additive hazards model estimates the difference in hazards and has an intuitive biological interpretation. The proposed weighted estimators for the additive hazards model use incomplete data nonparametrically and have close-form expressions. We show that they are consistent and asymptotically normal, and are more efficient than the simple weighted estimator which only uses the complete data. We illustrate their finite-sample performance through simulation studies and an application to study the progression from mild cognitive impairment to dementia using data from the Alzheimer’s Disease Neuroimaging Initiative as well as an application to the mouse leukemia study.

Suggested Citation

  • Lihong Qi & Xu Zhang & Yanqing Sun & Lu Wang & Yichuan Zhao, 2019. "Weighted estimating equations for additive hazards models with missing covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(2), pages 365-387, April.
    • Handle: RePEc:spr:aistmt:v:71:y:2019:i:2:d:10.1007_s10463-018-0648-y
    DOI: 10.1007/s10463-018-0648-y
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    References listed on IDEAS

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    1. Qi, Lihong & Wang, C.Y. & Prentice, Ross L., 2005. "Weighted Estimators for Proportional Hazards Regression With Missing Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1250-1263, December.
    2. Mark, Steven D. & Katki, Hormuzd A., 2006. "Specifying and Implementing Nonparametric and Semiparametric Survival Estimators in Two-Stage (Nested) Cohort Studies With Missing Case Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 460-471, June.
    3. Wang, Suojin & Wang, C. Y., 2001. "A note on kernel assisted estimators in missing covariate regression," Statistics & Probability Letters, Elsevier, vol. 55(4), pages 439-449, December.
    4. C. Y. Wang & Hua Yun Chen, 2001. "Augmented Inverse Probability Weighted Estimator for Cox Missing Covariate Regression," Biometrics, The International Biometric Society, vol. 57(2), pages 414-419, June.
    5. Yanqing Sun & Xiyuan Qian & Qiong Shou & Peter B. Gilbert, 2017. "Analysis of two-phase sampling data with semiparametric additive hazards models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 377-399, July.
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