We propose new simultaneous inference methods for diagnostic trials with elaborate factorial designs. Instead of the commonly used total area under the receiver operating characteristic (ROC) curve, our parameters of interest are partial areas under ROC curve segments that represent clinically relevant biomarker cut-off values. We construct a nonparametric multiple contrast test for these parameters and show that it asymptotically controls the family-wise type one error rate. Finite sample properties of this test are investigated in a series of computer experiments. We provide empirical and theoretical evidence supporting the conjecture that statistical inference about partial areas under ROC curves is more efficient than inference about the total areas.

翻译：针对具有复杂析因设计的诊断试验，我们提出新的同时推断方法。与常用的受试者工作特征（ROC）曲线下总面积不同，我们关注的参数是代表临床相关生物标志物截断值的ROC曲线段下局部区域。我们为这些参数构建了非参数多重对比检验，并证明该方法渐近控制族系一类错误率。通过系列计算机实验研究了该检验的有限样本性质。我们提供的经验与理论证据支持以下猜想：关于ROC曲线下局部区域的统计推断比关于总面积的推断更有效率。