Results 271 to 280 of about 302,402 (283)
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Regression Models for Convex ROC Curves
Biometrics, 2000Summary. The performance of a diagnostic test is summarized by its receiver operating characteristic (ROC) curve. Under quite natural assumptions about the latent variable underlying the test, the ROC curve is convex. Empirical data on a test's performance often comes in the form of observed true positive and false positive relative frequencies under ...
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Receiver Operator Characteristic (ROC) Curves
Infection Control & Hospital Epidemiology, 1988The goal of diagnostic testing is to identify patients with a particular disease. Often, it is just as important that the test not mistakenly identify healthy persons as having disease. For example, a new test for the acquired immunodeficiency syndrome (AIDS) might identify 99.99% of all patients infected with the human immunodeficiency virus (HIV ...
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Targeting the poor using ROC curves
World Development, 1997Abstract This paper compares the performance of targeting indicators to identify the poor. If the ROC curve of one indicator lies above that of another, the first indicator dominates the second for all social welfare functions based on the two types of errors involved in targeting. The method is applied to Bangladesh.
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Pattern Recognition Letters, 2017
This paper shows that ROC curves that are constructed with nonrandom data are biased.The magnitude of this bias is explored using simulations.A procedure for plotting consistent ROC curves is introduced.The presented procedure works well with simulated and non-simulated data. This paper shows that when a classifier is evaluated with nonrandom test data,
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This paper shows that ROC curves that are constructed with nonrandom data are biased.The magnitude of this bias is explored using simulations.A procedure for plotting consistent ROC curves is introduced.The presented procedure works well with simulated and non-simulated data. This paper shows that when a classifier is evaluated with nonrandom test data,
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Efficient confidence bounds for ROC curves
Statistics in Medicine, 1994AbstractThe specificity and sensitivity of a quantitative diagnostic marker depends on the selected cut‐off point. The ROC curve is generated by plotting sensitivity against specificity as the cut‐off point runs through the whole range of possible marker values.
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