Evaluating diagnostic tests: The area under the ROC curve and the balance of errors.
Because accurate diagnosis lies at the heart of medicine, it is important to be able to evaluate the effectiveness of diagnostic tests. A variety of accuracy measures are used. One particularly widely used measure is the AUC, the area under the receiver operating characteristic (ROC) curve. This measure has a well-understood weakness when comparing ROC curves which cross. However, it also has the more fundamental weakness of failing to balance different kinds of misdiagnoses effectively. This is not merely an aspect of the inevitable arbitrariness in choosing a performance measure, but is a core property of the way the AUC is defined. This property is explored, and an alternative, the H measure, is described.
Hand
David J
DJ
Imperial College, London. d.j.hand@imperial.ac.uk
D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D003955:Diagnostic Tests, Routine / Q000592:standards*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D010024:Osteoporosis / Q000175:diagnosis; D012372:ROC Curve; D012680:Sensitivity and Specificity; D011795:Surveys and Questionnaires