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Acta Mathematica Sinica, English Series

, Volume 35, Issue 7, pp 1163–1178 | Cite as

Weighted Least Squares Method for the Accelerated Failure Time Model with Auxiliary Covariates

  • Ling Hui Jin
  • Yan Yan LiuEmail author
  • Lang Wu
Article
  • 4 Downloads

Abstract

This paper deals with the analysis of accelerated failure time model when the primary covariate is subject to missing. We assume that the true covariate is measured precisely on a randomly chosen validation set, whereas auxiliary information for primary covariate is available to all study subjects. The asymptotic properties for the proposed estimator are developed and the simulation studies show that the efficiency gain is remarkable compared to the method using only the validation sample. A real example is also provided as an illustration.

Keywords

Survival analysis accelerated failure time model auxiliary covariates validation sample weighted least squares estimation 

MR(2010) Subject Classification

62N01 62N02 

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Notes

Acknowledgements

This work is funded in part by the National Science Foundation of China grants NSFC (Grant No. 11571263). The authors very grateful to the helpful comments of the Co-Editor, Associate Editor and referees that substantially improved the presentation of the paper.

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Copyright information

© Springer-Verlag GmbH Germany & The Editorial Office of AMS 2019

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsWuhan UniversityWuhanP. R. China
  2. 2.City CollegeWuhan University of Science and TechnologyWuhanP. R. China
  3. 3.Department of StatisticsUniversity of British ColumbiaVancouverCanada

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