Bayesian ROC curve estimation under binormality using a rank likelihood

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 competitors. (c) 2008 Elsevier B.V. All rights reserved.