Model-based likelihood ratio confidence intervals for survival functions

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We introduce an adjusted likelihood ratio procedure for computing pointwise confidence intervals for survival functions from censored data. The test statistic, scaled by a ratio of two variance quantities, is shown to converge to a chi-squared distribution with one degree of freedom. The confidence intervals are seen to be a neighborhood of a semiparametric survival function estimator and are shown to have correct empirical coverage. Numerical studies also indicate that the proposed intervals have smaller estimated mean lengths in comparison to the ones that are produced as a neighborhood of the Kaplan-Meier estimator. We illustrate our method using a lung cancer data set.

Original languageEnglish (US)
Pages (from-to)626-635
Number of pages10
JournalStatistics and Probability Letters
Volume82
Issue number3
DOIs
StatePublished - Mar 1 2012

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • Gaussian process
  • Lagrange multiplier
  • Maximum likelihood estimate
  • Misspecified model
  • Semiparametric random censorship model

Fingerprint Dive into the research topics of 'Model-based likelihood ratio confidence intervals for survival functions'. Together they form a unique fingerprint.

Cite this