An ROC-type measure of diagnostic accuracy when the gold standard is continuous-scale
- 1 January 2005
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 25 (3), 481-493
- https://doi.org/10.1002/sim.2228
Abstract
ROC curves and summary measures of accuracy derived from them, such as the area under the ROC curve, have become the standard for describing and comparing the accuracy of diagnostic tests. Methods for estimating ROC curves rely on the existence of a gold standard which dichotomizes patients into disease present or absent. There are, however, many examples of diagnostic tests whose gold standards are not binary‐scale, but rather continuous‐scale. Unnatural dichotomization of these gold standards leads to bias and inconsistency in estimates of diagnostic accuracy. In this paper, we propose a non‐parametric estimator of diagnostic test accuracy which does not require dichotomization of the gold standard. This estimator has an interpretation analogous to the area under the ROC curve. We propose a confidence interval for test accuracy and a statistical test for comparing accuracies of tests from paired designs. We compare the performance (i.e. CI coverage, type I error rate, power) of the proposed methods with several alternatives. An example is presented where the accuracies of two quick blood tests for measuring serum iron concentrations are estimated and compared. Copyright © 2005 John Wiley & Sons, Ltd.Keywords
This publication has 30 references indexed in Scilit:
- Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimationStatistics in Medicine, 2004
- Receiver operating characteristic (ROC) analysis for diagnostic examinations with uninterpretable casesStatistics in Medicine, 2002
- Discriminating Between Iron Deficiency Anemia and Anemia of Chronic Disease Using Traditional Indices of Iron Status vs Transferrin Receptor ConcentrationAmerican Journal of Clinical Pathology, 2001
- Three-way ROCsMedical Decision Making, 1999
- The area above the ordinal dominance graph and the area below the receiver operating characteristic graphJournal of Mathematical Psychology, 1975
- On Comparing the Correlations within Two Pairs of VariablesBiometrics, 1968
- Statistical MethodsSoil Science, 1957