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The effect of random measurement error on receiver operating characteristic (ROC) curves

Statistics in Medicine, 2000
In this paper confidence intervals for the area under the ROC curve are adjusted for the presence of measurement error. A parametric normal model is assumed. The ratio of intra-individual to inter-individual variance provides a relative measure of the amount of measurement error. An exact adjusted confidence interval is developed for the equal variance
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Receiver operating characteristic (ROC) curves: review of methods with applications in diagnostic medicine

Physics in Medicine & Biology, 2018
Abstract Receiver operating characteristic (ROC) analysis is a tool used to describe the discrimination accuracy of a diagnostic test or prediction model. While sensitivity and specificity are the basic metrics of accuracy, they have many limitations when characterizing test accuracy, particularly when comparing the accuracies of ...
Nancy A Obuchowski, Jennifer A Bullen
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Receiver operator characteristic (ROC) curves and non‐normal data: An empirical study

Statistics in Medicine, 1990
AbstractThis paper evaluates the performance of several diagnostic kits for assessing levels of serum prostatic acid phosphatase on patients at different stages of cancer of the prostate. Each patient was studied with several kits. We compare results obtained for receiver operator characteristic (ROC) curve methodology with data assumed to follow a ...
M J, Goddard, I, Hinberg
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On the Consistent Estimation of Optimal Receiver Operating Characteristic (ROC) Curve

Advances in Neural Information Processing Systems 35, 2022
Renxiong Liu, Yunzhang Zhu
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[ROC (receiver operating characteristics) curve: principles and application in biology].

Annales de biologie clinique, 2005
Laboratory test's diagnostic performances are generally estimated by means of their sensibility, specificity and positive and negative predictive values. Unfortunately, these indices reflect only imperfectly the capacity of a test to correctly classify subjects into clinically relevant subgroups.
H, Delacour   +4 more
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