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Regression Analysis of Length-biased and Right-censored Failure Time Data with Missing Covariates

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  • Na Hu
  • Xuerong Chen
  • Jianguo Sun

Abstract

type="main" xml:id="sjos12115-abs-0001"> Length-biased and right-censored failure time data arise from many fields, and their analysis has recently attracted a great deal of attention. Two examples of the areas that often produce such data are epidemiological studies and cancer screening trials. In this paper, we discuss regression analysis of such data in the presence of missing covariates, for which no established inference procedure seems to exist. For the problem, we consider the data arising from the proportional hazards model and propose two inverse probability weighted estimation procedures. The asymptotic properties of the resulting estimators are established, and the extensive simulation study conducted for the evaluation of the proposed methods suggests that they work well for practical situations.

Suggested Citation

  • Na Hu & Xuerong Chen & Jianguo Sun, 2015. "Regression Analysis of Length-biased and Right-censored Failure Time Data with Missing Covariates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 438-452, June.
    • Handle: RePEc:bla:scjsta:v:42:y:2015:i:2:p:438-452
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    File URL: http://hdl.handle.net/10.1111/sjos.12115
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    References listed on IDEAS

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    Cited by:

    1. Du, Mingyue & Li, Huiqiong & Sun, Jianguo, 2021. "Regression analysis of censored data with nonignorable missing covariates and application to Alzheimer Disease," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).

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