Confidence interval estimation of the difference between paired AUCs based on combined biomarkers

Lili Tian, Albert Vexler, Li Yan, Enrique F. Schisterman

Research output: Contribution to journalArticle

Abstract

In many diagnostic studies, multiple diagnostic tests are performed on each subject or multiple disease markers are available. Commonly, the information should be combined to improve the diagnostic accuracy. We consider the problem of comparing the discriminatory abilities between two groups of biomarkers. Specifically, this article focuses on confidence interval estimation of the difference between paired AUCs based on optimally combined markers under the assumption of multivariate normality. Simulation studies demonstrate that the proposed generalized variable approach provides confidence intervals with satisfying coverage probabilities at finite sample sizes. The proposed method can also easily provide P-values for hypothesis testing. Application to analysis of a subset of data from a study on coronary heart disease illustrates the utility of the method in practice.

Original languageEnglish (US)
Pages (from-to)3725-3732
Number of pages8
JournalJournal of Statistical Planning and Inference
Volume139
Issue number10
DOIs
Publication statusPublished - Oct 1 2009
Externally publishedYes

    Fingerprint

Keywords

  • Generalized pivot
  • Generalized test variable
  • Optimal linear combinations
  • Receiver operating characteristic (ROC) curve

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Statistics and Probability

Cite this