ROC analysis: comparison between the binormal and the Neyman-Pearson model

ROC analysis, a technique widely used to evaluate performance of human observers and medical diagnostic equipment is based on a binormal model, which leads to unrealistic results under many conditions. This paper develops a binormal Neyman-Pearson (BNP) formulation for ROC curves. Comparison shows significant superiority of the BNP model: the results are more accurate, more reliable and applicable to various relationships among the populations´ parameters. The formulation is well suited to the statistical estimation of ROC parameters from categorical data from computer and human observer studies.