Johnson Nils P
College of Physicians and Surgeons, Columbia University, 630 W. 168th St., New York, NY 10032, U.S.A.
Stat Med. 2004 Jul 30;23(14):2257-66. doi: 10.1002/sim.1835.
Traditionally, the receiver operating characteristic (ROC) curve for a diagnostic test plots true positives (sensitivity) against false positives (one minus specificity). However, this representation brings with it several drawbacks. A transformation to positive and negative likelihood ratio co-ordinates, scaled by base-ten logarithms, offers several advantages. First we motivate the use of positive and negative likelihood ratios, emphasizing their relationship to modification of the odds ratio. Then we highlight properties of likelihood ratios using the traditional ROC axes. Finally, we demonstrate ROC curves and their properties after conversion to likelihood ratio co-ordinates. These graphs do not waste space for tests lacking diagnostic power, and offer a simple visual assessment of a test's impact on the odds ratio.
传统上,诊断试验的受试者工作特征(ROC)曲线绘制的是真阳性率(灵敏度)与假阳性率(1减去特异度)。然而,这种表示方式存在几个缺点。转换为以常用对数缩放的阳性和阴性似然比坐标具有几个优点。首先,我们阐述使用阳性和阴性似然比的动机,强调它们与比值比修正的关系。然后,我们使用传统的ROC轴突出似然比的特性。最后,我们展示转换为似然比坐标后的ROC曲线及其特性。这些图形不会为缺乏诊断能力的试验浪费空间,并且能对试验对比值比的影响提供简单的直观评估。