Journal of Data Science

Abstract: Believe the Positive (BP) and Believe the Negative (BN) rules for combining two continuous diagnostic tests are compared with proce dures based on likelihood ratio and linear combination of the two tests. The sensitivity-specificity relationship for BP/BN is illustrated through a graph ical presentation of a ”ROC surface”, which leads to a natural approach of choosing between BP and BN. With a bivariate normal model, it is shown that the discriminating power of this approach is higher when the correla tion between the two tests has different signs for non-diseased and diseased population, given the location and variations of the two distributions are fixed. The idea is illustrated through an example.