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.