An improved measure for comparing diagnostic tests.
We present a loss based method for comparing the predictive performance of diagnostic tests. Unlike standard assessment mechanisms, like the area under the receiver-operating characteristic curve and the misclassification rate, our method takes specific advantage of any information that can be obtained about misclassification costs. We argue that not taking costs into account can lead to incorrect conclusions, and illustrate with two examples.
Adams
N M
NM
Department of Mathematics, Imperial College, London, UK. n.adams@ic.ac.uk
Hand
D J
DJ
D003365:Costs and Cost Analysis; D003951:Diagnostic Errors / Q000191:economics; D019937:Diagnostic Techniques and Procedures / Q000145:classification*; D016002:Discriminant Analysis; D006331:Heart Diseases / Q000175:diagnosis; D006801:Humans; D016015:Logistic Models; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity