Analyse-it
Analyse-it
  • Products
  • Pricing
  • Support
  • About us
Download trial Sign in
  • Statistical Reference Guide
  • Diagnostic performance

Area under the curve (AUC)

The area under (a ROC) curve is a measure of the accuracy of a quantitative diagnostic test.

A point estimate of the AUC of the empirical ROC curve is the Mann-Whitney U estimator (DeLong et. al., 1988). The confidence interval for AUC indicates the uncertainty of the estimate and uses the Wald Z large sample normal approximation (DeLong et al., 1998). A test with no better accuracy than chance has an AUC of 0.5, a test with perfect accuracy has an AUC of 1.

The interpretation of the AUC is:
  • The average value of sensitivity for all possible values of specificity (Zhou, Obuchowski, McClish, 2001).
  • The average value of specificity for all possible values of sensitivity (Zhou, Obuchowski, McClish, 2001).
  • The probability that a randomly selected subject with the condition has a test result indicating greater suspicion than that of a randomly chosen subject without the condition (Hanley & McNeil, 1982).

AUC can be misleading as it gives equal weight to the full range of sensitivity and specificity values even though a limited range, or specific threshold, may be of practical interest.

Related concepts
ROC plot
Difference between the areas under two curves
Related tasks
Plotting a single ROC curve
Comparing two or more ROC curves
Testing the area under the curve
Related information
Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29-36.
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988). Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics, 837-845.
Zhou, X. H., Obuchowski, N. A., & McClish, D. K. (2011). Statistical methods in diagnostic medicine. Wiley-Blackwell.
Available in Analyse-it Editions
Method Validation edition
Ultimate edition

  •  What is Analyse-it?
  •  What's new?
  •  Administrator's Guide
  •  User's Guide
  •  Statistical Reference Guide
  •  Distribution
  •  Compare groups
  •  Compare pairs
  •  Contingency tables
  •  Correlation and association
  •  Principal component analysis (PCA)
  •  Factor analysis (FA)
  •  Item reliability
  •  Fit model
  •  Method comparison / Agreement
  •  Measurement systems analysis (MSA)
  •  Reference interval
  •  Diagnostic performance
  •  Measures of diagnostic accuracy
  •  Estimating sensitivity and specificity of a diagnostic test
  •  Comparing the sensitivity and specificity two diagnostic tests
  •  ROC plot
  •  Plotting a single ROC curve
  •  Comparing two or more ROC curves
  •  Area under the curve (AUC)
  •  Testing the area under the curve
  •  Difference between the areas under two curves
  •  Testing the difference between the areas under two curves
  •  Decision thresholds
  •  Decision plot
  •  Finding the optimal decision threshold
  •  Predicting the decision threshold
  •  Study design
  •  Survival/Reliability
  •  Control charts
  •  Process capability
  •  Pareto analysis
  •  Study Designs
  •  Bibliography



Version 6.15
Published 18-Apr-2023
Products
  • Standard Edition
  • Medical Edition
  • Quality Control & Improvement Edition
  • Method Validation Edition
  • Ultimate Edition
  • Compare Editions
  • Pricing
Support
  • Documentation
  • Tutorials
  • Download latest version
  • Release history
  • Contact support
Company
  • About us
  • Blog
  • Contact us
  • Privacy policy

Get Started

  • Download free trial
  • Sign In

© 2026 Analyse-it® Software, Ltd. All rights reserved.

Statistical analysis and method validation software for Microsoft Excel.

We use essential cookies to run the site, and optional analytics to improve the experience for visitors. For more information see our Privacy policy.