Bivariate Test for testing the average areas under correlated receiver operating characteristic curves

Seneratna, D.; Sooriyarachchi, M.R.; Meyen, A.N.

dc.contributor.author	Seneratna, D.
dc.contributor.author	Sooriyarachchi, M.R.
dc.contributor.author	Meyen, A.N.
dc.date.accessioned	2021-07-07T03:25:40Z
dc.date.available	2021-07-07T03:25:40Z
dc.date.issued	2015
dc.identifier.citation	Seneratna, D. Sooriyarachchi, M.R., Meyen, A.N. (2015) Bivariate Test for testing the average areas under correlated receiver operating characteristic curves. American Journal of Applied Mathematics and Statistics Vol. 3, No. 5, 2015, pp 190-198. doi: 10.12691/ajams-3-5-3.	en_US
dc.identifier.uri	http://archive.cmb.ac.lk:8080/xmlui/handle/70130/5464
dc.description.abstract	Methodology developed for comparing correlated ROC curves are mainly based on nonparametric methods. These nonparametric methods have several disadvantages. In this paper the authors propose an asymptotic bivariate test for comparing pairs of AUCs for independent data based on the Dorfman and Alf maximum likelihood approach. The properties of the test are examined by using simulation studies. The method is illustrated on an example of angiogram results from Sri Lanka. The test applied to the example found that there was a significant difference in the predictive power of three different cut-offs examined	en_US
dc.description.sponsorship	No sponsors	en_US
dc.language.iso	en	en_US
dc.subject	bivariate test, Receiving Operating Characteristic (ROC) curve, Area under the Curve (AUC), Beta Distribution, Angiogram, Cardiac Stress Test (CST)	en_US
dc.title	Bivariate Test for testing the average areas under correlated receiver operating characteristic curves	en_US
dc.type	Article	en_US