The area under a receiver operating characteristic curve (AUC) is a useful tool to assess the performance of continuous-scale diagnostic tests on binary classification. In this article, we propose an empirical likelihood (EL) method to construct confidence intervals for the AUC from data collected by ranked set sampling (RSS). The proposed EL-based method enables inferences without assumptions required in existing nonparametric methods and takes advantage of the sampling efficiency of RSS. We show that for both balanced and unbalanced RSS, the EL-based point estimate is the Mann-Whitney statistic, and confidence intervals can be obtained from a scaled chi-square distribution. Simulation studies and real data analysis show that the proposed method outperforms the existing methods.

翻译：接收器操作特征曲线(AUC)下的区域是评估二进制分类连续规模诊断测试的性能的有用工具,在本条中,我们提议了一种经验可能性(EL)方法,用按等级排列的抽样收集的数据为AUC建立信任间隔。拟议的EL方法使得在没有现有非参数方法所需假设的情况下可以推断,并利用RSS的取样效率。我们表明,对于平衡和不平衡的RSS,基于EL的点估计值是曼-威特尼统计,而从按比例的基平方分布中可以取得信任间隔。模拟研究和真实数据分析表明,拟议的方法优于现有方法。