Skip to main navigation Skip to search Skip to main content

Semiparametric inference for ROC curves with censoring

  • Hua Liang*
  • , Yong Zhou
  • *Corresponding author for this work
  • University of Rochester
  • Shanghai University of Finance and Economics
  • CAS - Academy of Mathematics and System Sciences

Research output: Contribution to journalArticlepeer-review

Abstract

Comparison of two samples can sometimes be conducted on the basis of analysis of receiver operating characteristic (ROC) curves. A variety of methods of point estimation and confidence intervals for ROC curves have been proposed and well studied. We develop smoothed empirical likelihood-based confidence intervals for ROC curves when the samples are censored and generated from semiparametric models. The resulting empirical log-likelihood function is shown to be asymptotically chi-squared. Simulation studies illustrate that the proposed empirical likelihood confidence interval is advantageous over the normal approximation-based confidence interval. A real data set is analysed using the proposed method.

Original languageEnglish
Pages (from-to)212-227
Number of pages16
JournalScandinavian Journal of Statistics
Volume35
Issue number2
DOIs
StatePublished - Jun 2008
Externally publishedYes

Keywords

  • Confidence interval
  • Coverage
  • Empirical likelihood function
  • Empirical likelihood ratio
  • Estimating equation
  • Kaplan-Meier estimation

Fingerprint

Dive into the research topics of 'Semiparametric inference for ROC curves with censoring'. Together they form a unique fingerprint.

Cite this