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Estimation of the area under the ROC curve
Author(s) -
Faraggi David,
Reiser Benjamin
Publication year - 2002
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1228
Subject(s) - normality , statistics , receiver operating characteristic , statistic , kernel (algebra) , kernel smoother , smoothing , mathematics , mean squared error , computer science , econometrics , kernel method , artificial intelligence , radial basis function kernel , support vector machine , combinatorics
The area under the receiver operating characteristic curve is frequently used as a measure for the effectiveness of diagnostic markers. In this paper we discuss and compare estimation procedures for this area. These are based on (i) the Mann–Whitney statistic; (ii) kernel smoothing; (iii) normal assumptions; (iv) empirical transformations to normality. These are compared in terms of bias and root mean square error in a large variety of situations by means of an extensive simulation study. Overall we find that transforming to normality usually is to be preferred except for bimodal cases where kernel methods can be effective. Copyright 2002 John Wiley & Sons, Ltd.