An Exponential Model Used for optimal Threshold selection on ROC Curues
- 1 June 1988
- journal article
- research article
- Published by SAGE Publications in Medical Decision Making
- Vol. 8 (2) , 120-131
- https://doi.org/10.1177/0272989x8800800208
Abstract
A two-parameter exponential equation for modeling a receiver operating characteristic (ROC) curve is presented, where the area under the curve is a simple function of one of the parameters. The model makes no distributional assumptions about the underlying normal and abnormal patient populations or about the shape of the resulting ROC curves. In a computer simulation of 75 ROC curves, the model provides a fit equivalent to the maximum likelihood estimate method commonly used for ROC curve fitting. Similar results are obtained using the model to fit ROC curve data from the literature. The model's equation calculates the true-positive ratio as a function of the false-positive ratio, and has a first derivative that is useful for finding the optimal decision threshold for a diagnostic testing procedure. In particular, the model is useful in a computer program for finding jointly optimal thresholds for multiple sequential tests. Key words: receiver operating characteristic (ROC) curve; decision theory; optimization; computer simulation. (Med Decis Making 8:120-131, 1988)This publication has 8 references indexed in Scilit:
- The Simulation of Logical Networks (SLN)SIMULATION, 1984
- Comparison of Five Digital Scintigraphic Display ModesMedical Decision Making, 1983
- The meaning and use of the area under a receiver operating characteristic (ROC) curve.Radiology, 1982
- ROC curve estimation and hypothesis testing: applications to breast cancer detectionPattern Recognition, 1982
- Basic principles of ROC analysisSeminars in Nuclear Medicine, 1978
- Caveat on Use of the Parameterd'for Evaluation of Observer PerformanceRadiology, 1973
- Maximum-likelihood estimation of parameters of signal-detection theory and determination of confidence intervals—Rating-method dataJournal of Mathematical Psychology, 1969
- A Maximum Likelihood Solution for the Method of Successive Intervals Allowing for Unequal Stimulus DispersionsPsychometrika, 1967