McClish D K
Department of Biostatistics, Medical College of Virginia, Richmond 23298.
Med Decis Making. 1989 Jul-Sep;9(3):190-5. doi: 10.1177/0272989X8900900307.
The area under the ROC curve is a common index summarizing the information contained in the curve. When comparing two ROC curves, though, problems arise when interest does not lie in the entire range of false-positive rates (and hence the entire area). Numerical integration is suggested for evaluating the area under a portion of the ROC curve. Variance estimates are derived. The method is applicable for either continuous or rating scale binormal data, from independent or dependent samples. An example is presented which looks at rating scale data of computed tomographic scans of the head with and without concomitant use of clinical history. The areas under the two ROC curves over an a priori range of false-positive rates are examined, as well as the areas under the two curves at a specific point.
ROC曲线下面积是一个总结曲线中所含信息的常用指标。然而，在比较两条ROC曲线时，如果关注的不是假阳性率的整个范围（以及因此不是整个面积），就会出现问题。建议采用数值积分来评估ROC曲线一部分下的面积。推导了方差估计值。该方法适用于来自独立或相关样本的连续或等级量表双正态数据。给出了一个例子，该例子研究了在有和没有同时使用临床病史的情况下头部计算机断层扫描的等级量表数据。研究了两条ROC曲线在假阳性率的先验范围内的面积，以及两条曲线在特定点处的面积。
