Bootstrap Confidence Intervals for an Adjusted Survivor Function under the Dependent Censoring Model

  • Lee, Seung-Yeoun (Department of Applied Mathematics, Sejong University) ;
  • Sok, Yong-U (Department of Applied Mathematics, Sejong University)
  • Published : 2001.04.01

Abstract

In this paper, we consider a simple method for testing the assumption of independent censoring on the basis of a Cox proportional hazards regression model with a time-dependent covariate. This method involves a two-stage sampling in which a random subset of censored observations is selected and followed-up until their true survival times are observed. Lee and Wolfe(1998) proposed an adjusted estimate of the survivor function for the dependent censoring under a proportional hazards alternative. This paper extends their result to obtain a bootstrap confidence interval for the adjusted survivor function under the dependent censoring. The proposed procedure is illustrated with an example of a clinical trial for lung cancer analysed in Lee and Wolfe(1998).

Keywords

References

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