Hotilovac Lejla
Department of Mathematics and Statistics, Georgia State University, 30 Pryor Street, Atlanta, GA 30303, USA.
Stat Methods Med Res. 2008 Apr;17(2):207-21. doi: 10.1177/0962280207087173.
The accuracy of a diagnostic test with continuous-scale results is of high importance in clinical medicine. It is often summarised by the area under the ROC curve (AUC). In this article, we discuss and compare nine non-parametric confidence intervals of the AUC for a continuous-scale diagnostic test. Simulation studies are conducted to evaluate the relative performance of the confidence intervals for the AUC in terms of coverage probability and average interval length. A real example is used to illustrate the application of the recommended methods.
在临床医学中,具有连续尺度结果的诊断测试的准确性至关重要。它通常由ROC曲线下面积(AUC)来概括。在本文中,我们讨论并比较了连续尺度诊断测试中AUC的九个非参数置信区间。进行了模拟研究,以根据覆盖概率和平均区间长度评估AUC置信区间的相对性能。使用一个实际例子来说明推荐方法的应用。