Author： Zou K. H.
Publisher： Taylor & Francis Ltd
ISSN： 1360-0532
Source： Journal of Applied Statistics, Vol.27, Iss.5, 2000-07, pp. : 621-631
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
A receiver operating characteristic (ROC) curve is a plot of two survival functions, derived separately from the diseased and healthy samples. A special feature is that the ROC curve is invariant to any monotone transformation of the measurement scale. We propose and analyse semiparametric and parametric transformation models for this two-sample problem. Following an unspecified or specified monotone transformation, we assume that the healthy and diseased measurements have two normal distributions with different means and variances. Maximum likelihood algorithms for estimating ROC curve parameters are developed. The proposed methods are illustrated on the marker CA125 in the diagnosis of gastric cancer.
Related content
A Flexible Method for Estimating the ROC Curve
By Haobo Ren
Journal of Applied Statistics, Vol. 31, Iss. 7, 2004-08 ,pp. :
Access to resources
Recommend
Confidence intervals and bands for the binormal ROC curve revisited
Journal of Applied Statistics, Vol. 39, Iss. 1, 2012-01 ,pp. :
Exact Bootstrap Variances of the Area Under ROC Curve
Communications in Statistics: Theory and Methods, Vol. 36, Iss. 13, 2007-10 ,pp. :