Equivalence of binormal likelihood-ratio and bi-chi-squared ROC curve models.

ABSTRACT: A basic assumption for a meaningful diagnostic decision variable is that there is a monotone relationship between it and its likelihood ratio. This relationship, however, generally does not hold for a decision variable that results in a binormal receiver operating characteristic (ROC) curve. As a result, ROC curve estimation based on the assumption of a binormal ROC-curve model produces improper ROC curves, which have 'hooks', are not concave over the entire domain and cross the chance line. Although in practice this 'improperness' is usually not noticeable, sometimes it is evident and problematic. To avoid this problem, Metz and Pan proposed basing ROC-curve estimation on the assumption of a binormal likelihood-ratio (binormal-LR) model, which states that the decision variable is an incre

SUBMITTER: Hillis SL 

PROVIDER: S-EPMC5570585 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature