title: Comparison of Paired ROC Curves through a Two-Stage Test.
abstract: The area under the receiver operating characteristic (ROC) curve (AUC) is a popularly used index when comparing two ROC curves. Statistical tests based on it for analyzing the difference have been well developed. However, this index is less informative when two ROC curves cross and have similar AUCs. In order to detect differences between ROC curves in such situations, a two-stage nonparametric test that uses a shifted area under the ROC curve (sAUC), along with AUCs, is proposed for paired designs. The new procedure is shown, numerically, to be effective in terms of power under a wide range of scenarios; additionally, it outperforms two conventional ROC-type tests, especially when two ROC curves cross each other and have similar AUCs. Larger sAUC implies larger partial AUC at the range of low false-positive rates in this case. Because high specificity is important in many classification tasks, such as medical diagnosis, this is an appealing characteristic. The test also implicitly analyzes the equality of two commonly used binormal ROC curves at every operating point. We also apply the proposed method to synthesized data and two real examples to illustrate its usefulness in practice.
authors.affiliation: a Department of Statistics , Chonnam National University , Gwangju , South Korea.
authors.forename: Wenbao
authors.initials: W
authors.lastname: Yu
authors.forename: Eunsik
authors.initials: E
authors.lastname: Park
authors.forename: Yuan-Chin Ivan
authors.initials: YC
authors.lastname: Chang
mesh_terms: D019540:Area Under Curve; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D046169:Dermoscopy / Q000706:statistics & numerical data; D006801:Humans; D008545:Melanoma / Q000473:pathology; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D011237:Predictive Value of Tests; D012372:ROC Curve; D012107:Research Design / Q000706:statistics & numerical data*; D012878:Skin Neoplasms / Q000473:pathology; D018709:Statistics, Nonparametric
keywords: AUC; Nonparametric test; Two-stage test; sAUC