In this paper, we propose a new semi-parametric maximum likelihood (ML) estimate of a receiver operating characteristic (ROC) curve that satisfies the property of invariance of the ROC curve and is easy to compute. We show that our new estimator is sqrt[n]-consistent and has an asymptotically normal distribution. Our extensive simulation studies show that the proposed method is efficient and ro...

The covariate-specific receiver operating characteristic curve is frequently used to evaluate the classification accuracy of a diagnostic test when it is associated with certain covariates. In this paper, we proposed a new procedure for estimating this curve based on a reformulation of the conventional location-scale model as well as the idea of composite quantile regression. Asymptotic normali...

ROC curve analysis is used widely in medicine as a method for evaluating the performance of diagnostic tests (3,5,6,10), but has been used recently in many agricultural applications (2,4,5,11,12). The ROC curve provides information regarding how often a test’s predictions are correct, and provides a graphical method for evaluating and discriminating between different diagnostic tests or modific...

There are various methods to estimate the parameters in the binormal model for the ROC curve. In this paper, we propose a conceptually simple and computationally feasible Bayesian estimation method using a rank-based likelihood. Posterior consistency is also established. We compare the new method with other estimation methods and conclude that our estimator generally performs better than its co...

Uplift modeling is a classification method that determines the incremental impact of an action on a given population. Uplift modeling aims at maximizing the area under the uplift curve, which is the difference between the subject and control sets’ area under the lift curve. Lift and uplift curves are seldom used outside of the marketing domain, whereas the related ROC curve is frequently used i...

Multiple diagnostic tools are used by emergency physicians, every day. In addition, new tools are evaluated to obtain more accurate methods and reduce time or cost of conventional ones. In the previous parts of this educational series, we described diagnostic performance characteristics of diagnostic tests including sensitivity, specificity, positive and negative predictive values, and likeliho...

Sensitivity and specificity are two components that measure the inherent validity of a diagnostic test for dichotomous outcomes against a gold standard. Receiver operating characteristic (ROC) curve is the plot that depicts the trade-off between the sensitivity and (1-specificity) across a series of cut-off points when the diagnostic test is continuous or on ordinal scale (minimum 5 categories)...

We are developing a computer-aided diagnosis (CAD) system for lung nodule detection on thoracic helical computed tomography (CT) images. In the first stage of this CAD system, lung regions are identified by a k-means clustering technique. Each lung slice is classified as belonging to the upper, middle, or the lower part of the lung volume. Within each lung region, structures are segmented again...