Optimal Combinations of Diagnostic Tests Based on AUC

Xin Huang, Gengsheng Qin, Yixin Fang

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

When several diagnostic tests are available, one can combine them to achieve better diagnostic accuracy. This article considers the optimal linear combination that maximizes thearea under the receiver operating characteristic curve(AUC); the estimates of the combination's coefficients can be obtained via a nonparametric procedure. However, for estimating the AUC associated with the estimated coefficients, the apparent estimation by re-substitution is too optimistic. To adjust for the upward bias, several methods are proposed. Among them the cross-validation approach is especially advocated, and an approximated cross-validation is developed to reduce the computational cost. Furthermore, these proposed methods can be applied for variable selection to select important diagnostic tests. The proposed methods are examined through simulation studies and applications to three real examples.

Original languageEnglish (US)
Pages (from-to)568-576
Number of pages9
JournalBiometrics
Volume67
Issue number2
DOIs
StatePublished - Jun 2011

All Science Journal Classification (ASJC) codes

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

Keywords

  • Cross-validation
  • Over-fitting
  • ROC curve
  • Variable selection

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