Exact confidence interval estimation for the Youden index and its corresponding optimal cut-point

Chin Ying Lai, Lili Tian, Enrique F. Schisterman

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


In diagnostic studies, the receiver operating characteristic (ROC) curve and the area under the ROC curve are important tools in assessing the utility of biomarkers in discriminating between non-diseased and diseased populations. For classifying a patient into the non-diseased or diseased group, an optimal cut-point of a continuous biomarker is desirable. Youden's index (J), defined as the maximum vertical distance between the ROC curve and the diagonal line, serves as another global measure of overall diagnostic accuracy and can be used in choosing an optimal cut-point. The proposed approach is to make use of a generalized approach to estimate the confidence intervals of the Youden index and its corresponding optimal cut-point. Simulation results are provided for comparing the coverage probabilities of the confidence intervals based on the proposed method with those based on the large sample method and the parametric bootstrap method. Finally, the proposed method is illustrated via an application to a data set from a study on Duchenne muscular dystrophy (DMD).

Original languageEnglish (US)
Pages (from-to)1103-1114
Number of pages12
JournalComputational Statistics and Data Analysis
Issue number5
StatePublished - May 1 2012
Externally publishedYes


  • Confidence interval
  • Generalized pivotal quantity
  • Optimal cut-point
  • ROC curve
  • Sensitivity and specificity
  • Youden index

ASJC Scopus subject areas

  • Computational Mathematics
  • Computational Theory and Mathematics
  • Statistics and Probability
  • Applied Mathematics


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