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Article
The Probability Mass Function of the Kaplan-Meier Product-Limit Estimator
The American Statistician (2022)
  • Lawrence Leemis, William & Mary
  • Yuxin Qin, William & Mary
  • Heather Sasinowska
Abstract
Kaplan and Meier’s 1958 article developed a nonparametric estimator of the survivor function from a rightcensored dataset. Determining the size of the support of the estimator as a function of the sample size provides a challenging exercise for students in an advanced course in mathematical statistics. We devise two algorithms for calculating the support size and calculate the associated probability mass function for small sample sizes and particular probability distributions for the failure and censoring times.
Keywords
  • Censoring,
  • Induction,
  • Nonparametric estimation,
  • Probability mass function,
  • Survival analysis,
  • Survivor function
Publication Date
Spring May 24, 2022
DOI
https://doi.org/10.1080/00031305.2022.2070279
Publisher Statement
Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=utas20
Citation Information
Yuxin Qin, Heather Sasinowska & Lawrence Leemis (2022): The Probability Mass Function of the Kaplan–Meier Product–Limit Estimator, The American Statistician, DOI: 10.1080/00031305.2022.2070279