Darrin C Edwards1. 1. The Department of Physiology, 303 E Superior St., Northwestern University, Chicago, IL 60611, USA. darrin.c.edwards@gmail.com
Abstract
RATIONALE AND OBJECTIVES: Traditional two-class receiver operating characteristic (ROC) analysis is inadequate for the complete evaluation of observer performance in tasks with more than two classes. MATERIALS AND METHODS: Here, a Monte Carlo estimation method for operating point coordinates on a three-class ROC surface is developed and compared with analytically calculated coordinates in two special cases: (1) univariate and (2) restricted bivariate trinormal underlying data. RESULTS: In both cases, the statistical estimates were found to be good in the sense that the analytical values lay within the 95% confidence interval of the estimated values about 95% of the time. CONCLUSIONS: The statistical estimation method should be key in the development of a pragmatic performance metric for evaluation of observers in classification tasks with three or more classes.
RATIONALE AND OBJECTIVES: Traditional two-class receiver operating characteristic (ROC) analysis is inadequate for the complete evaluation of observer performance in tasks with more than two classes. MATERIALS AND METHODS: Here, a Monte Carlo estimation method for operating point coordinates on a three-class ROC surface is developed and compared with analytically calculated coordinates in two special cases: (1) univariate and (2) restricted bivariate trinormal underlying data. RESULTS: In both cases, the statistical estimates were found to be good in the sense that the analytical values lay within the 95% confidence interval of the estimated values about 95% of the time. CONCLUSIONS: The statistical estimation method should be key in the development of a pragmatic performance metric for evaluation of observers in classification tasks with three or more classes.