  The receiver operating characteristic curve is widely applied in measuring
the performance of diagnostic tests. Many direct and indirect approaches have
been proposed for modelling the ROC curve, and because of its tractability, the
Gaussian distribution has typically been used to model both populations. We
propose using a Gaussian mixture model, leading to a more flexible approach
that better accounts for atypical data. Monte Carlo simulation is used to
circumvent the issue of absence of a closed-form. We show that our method
performs favourably when compared to the crude binormal curve and to the
semi-parametric frequentist binormal ROC using the famous LABROC procedure.
