Interval Censored Survival Data: A Review of Recent Progress

  • Jian Huang
  • Jon A. Wellner
Part of the Lecture Notes in Statistics book series (LNS, volume 123)


We review estimation in interval censoring models, including nonparametric estimation of a distribution function and estimation of regression models. In the nonparametric setting, we describe computational procedures and asymptotic properties of the nonparametric maximum likelihood estimators. In the regression setting, we focus on the proportional hazards, the proportional odds and the accelerated failure time semiparametric regression models. Particular emphasis is given to calculation of the Fisher information for the regression parameters. We also discuss computation of the regression parameter estimators via profile likelihood or maximization of the semiparametric likelihood, distributional results for the maximum likelihood estimators, and estimation of (asymptotic) variances. Some further problems and open questions are also reviewed.


Maximum Likelihood Estimator Efficient Score Asymptotic Normality Distributional Result Profile Likelihood 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York, Inc. 1997

Authors and Affiliations

  • Jian Huang
    • 1
  • Jon A. Wellner
    • 2
  1. 1.Department Of Statistics and Acturial ScienceUniversity of IowaIowa CityUSA
  2. 2.University of Washington StatisticsSeattleUSA

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