• There are currently no refbacks.

Copyright (c) 2015 Pakistan Journal of Statistics and Operation Research

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.


Evaluation of biomarker using two parameter bi-exponential ROC curve


Two parameter bi-exponential ROC model, AUC and variance of AUC, Monte Carlo simulation.


Receiver Operating Characteristic (ROC) Curve is used for assessing the ability of a biomarker/screening test to discriminate between non-diseased and diseased subject. In this paper, the parametric ROC curve is studied by assuming two-parameter exponential distribution to the biomarker values. The ROC model developed under this assumption is called bi-exponential ROC (EROC) model. Here, the research interest is to know how far the biomarker will make a distinction between diseased and non-diseased subjects when the gold standard is available using parametric EROC curve and its Area Under the EROC Curve (AUC).  Here, the standard error is used as an estimate of the precision of the accuracy measure AUC. The properties of EROC curve that explains the behavior of the EROC curve are also discussed. The AUC along with its asymptotic variance and confidence interval are derived.  





Pakistan Journal of Statistics and Operation Research; Vol. 11 No. 4, 2015

Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810