The area under the receiver-operating characteristic curve (AUC) has become a popular index not only for measuring the overall prediction capacity of a marker but also the association strength between continuous and binary variables. In the current study, it has been used for comparing the association size of four different interventions involving impulsive decision making, studied through an animal model, in which each animal provides several negative (pre-treatment) and positive (post-treatment) measures. The problem of the full comparison of the average AUCs arises therefore in a natural way. We construct an analysis of variance (ANOVA) type test for testing the equality of the impact of these treatments measured through the respective AUCs, and considering the random-effect represented by the animal. The use (and development) of a post-hoc Tukey's HSD type test is also considered. We explore the finite-sample behavior of our proposal via Monte Carlo simulations, and analyze the data generated from the original problem. An R package implementing the procedures is provided as supplementary material.

翻译：受试者工作特征曲线下面积（AUC）已成为衡量标记物整体预测能力以及连续变量与二元变量之间关联强度的流行指标。在本研究中，该指标被用于比较涉及冲动性决策的四种不同干预措施的关联强度，这些干预措施通过动物模型进行研究，每只动物提供多个阴性（治疗前）和阳性（治疗后）测量值。因此，完全比较平均AUC的问题自然产生。我们构建了一种方差分析（ANOVA）类型的检验，用于检验通过这些处理各自AUC衡量的效果是否相等，并考虑动物所代表的随机效应。同时，还考虑使用（并开发）事后Tukey HSD类型的检验。我们通过蒙特卡洛模拟探索了所提方法的有限样本行为，并分析了原始问题生成的数据。作为补充材料，提供了实现这些过程的R包。