Efficiency Loss with the Kaplan-Meier Estimator.

Abstract

We consider the proportional hazards model where the distribution G of the censoring random variable is related to the distribution F of the lifetime random variable via (1 - G)=(1 - F) to the beta power. Nonparametric estimators of F are developed for the case where beta is unknown and the case where beta is known. Of interest in their own right, these estimators also enable us to study the robustness of the Kaplan-Meier estimator (KME) in a nonparametric model for which it is not the preferred estimator. Comparisons are based on asymptotic efficiencies and exact mean square errors. We also compare the KME to the empirical survival function, thereby providing, in a nonparametric setting, a measure of the loss in efficiency due to the presence of censoring. Keywords: Censored model; Kaplan-Meier estimator; Proportional hazards.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1985
Accession Number
ADA161341

Entities

People

  • Frank Proschan
  • James Sconing
  • Myles Hollander

Organizations

  • Florida State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Data Science
  • Distribution Functions
  • Efficiency
  • Estimators
  • Gaussian Processes
  • Information Science
  • New York
  • Plastic Explosives
  • Probability
  • Random Variables
  • Scientific Research
  • Statistics
  • Survival
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Statistical inference.