Asymptotic Theory in Rank Estimation for AFT Model Under Fixed Censorship

  • Zhezhen Jin
  • Zhiliang Ying
Part of the Statistics for Industry and Technology book series (SIT)


Rank based parameter estimation in the accelerated failure time model with right-censoring has been studied rigorously by many authors [(1990), (1991) and (1993)]. A key assumption in establishing the asymptotic normality for the rank estimator is that, conditional on covariates, the censoring time has a density function. This assumption may be violated in many situations. It may also be non-intrinsic in that the limiting variance formula does not involve such a density. We show in this paper that the usual asymptotic theory for rank estimation can indeed be established without this stringent and unnatural assumption.


Accelerated failure time model asymptotic normality exponential inequality fixed censoring linear rank statistics survival data 


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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Zhezhen Jin
    • 1
  • Zhiliang Ying
    • 1
  1. 1.Department of Bio statisticsColumbia UniversityNew YorkUSA

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