Newcombe R G
University of Wales College of Medicine, Heath Park, Cardiff, CF14 4XN, UK.
Stat Med. 2001 Mar 30;20(6):907-15. doi: 10.1002/sim.906.
Often the performances of two binary diagnostic or screening tests are compared by applying them to the same set of subjects, some of whom are affected, some unaffected. The McNemar test, and corresponding interval estimation methods, may be used to compare the sensitivity of the two tests, but this disregards both any observed difference in specificity and its imprecision due to sampling variation. The suggested approach is to display point and interval estimates for a weighted mean f of the differences in sensitivity and specificity between the two tests. The mixing parameter lambda, which is allowed to range from 0 to 1, represents the prevalence in the population to which application is envisaged, together with the relative seriousness of false positives and false negatives. The confidence interval for f is obtained by a simple extension of a closed-form method for the paired difference of proportions, which has favourable coverage properties and is based on the Wilson single proportion score method. A plot of f against lambda is readily obtained using a Minitab macro.
通常，通过将两种二元诊断或筛查测试应用于同一组受试者（其中一些受影响，一些未受影响）来比较它们的性能。可以使用 McNemar 检验和相应的区间估计方法来比较两种测试的敏感性，但这忽略了观察到的特异性差异及其因抽样变异导致的不精确性。建议的方法是展示两种测试之间敏感性和特异性差异的加权均值 f 的点估计和区间估计。混合参数 lambda 的取值范围为 0 到 1，它代表了设想应用的人群中的患病率，以及假阳性和假阴性的相对严重性。f 的置信区间是通过对比例配对差异的封闭形式方法进行简单扩展而获得的，该方法具有良好的覆盖特性，并且基于 Wilson 单比例得分方法。使用 Minitab 宏可以轻松获得 f 与 lambda 的关系图。
