The paradoxical nature of the proportional hazards model of random censorship

Sándor Csörgo, Julian J. Faraway

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

We show that the proportional hazards model of random censorship is too good to be frequently true as measured by mean squared errors: for estimating the underlying distribution function F(x) it is better to have a censored sample for a suitable expected censoring proportion than an uncensored full sample of the same size for any x below the 0.56-quantile of F.

Original languageEnglish
Pages (from-to)67-78
Number of pages12
JournalStatistics
Volume31
Issue number1
DOIs
Publication statusPublished - 1 Jan 1998

Keywords

  • Censored and uncensored samples
  • Proportional hazards
  • Random censorship

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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