Symmetric tests and confidence intervals for survival probabilities and quantiles of censored survival data

Stuart Barber, Christopher Jennison

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


We describe existing tests and introduce two new tests concerning the value of a survival function. These tests may be used to construct a confidence interval for the survival probability at a given time or for a quantile of the survival distribution. Simulation studies show that error rates can differ substantially from their nominal values, particularly at survival probabilities close to zero or one. We recommend our new constrained bootstrap test for its good overall performance.

Original languageEnglish
Pages (from-to)430-436
Number of pages7
Issue number2
Publication statusPublished - 1 Jun 1999


  • Beta distribution
  • Bootstrap sampling
  • Censoring
  • Confidence interval
  • Greenwood's formula
  • Hypothesis test
  • Kaplan-Meier estimate
  • Likelihood ratio test
  • Survival data

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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