论文标题
Wilcoxon-Mann-Whitney效果集群数据：信息群集的大小
Wilcoxon-Mann-Whitney Effects for Clustered Data: Informative Cluster Size
论文作者
论文摘要
在聚类的数据设定中，信息群的大小一直是最近研究的重点。在非参数环境中，该问题主要用于测试分布功能的平等。本文的目的是为Wilcoxon-Mann-Whintey效应（也称为非主体相对效应）制定推论程序。提供了公正的估计器，并研究了其渐近性能。渐近理论被用来开发推论方法。当提出的方法在构造估算器时考虑了集群大小中的信息，但它同样适用于可忽略的群集大小情况。仿真结果表明，我们的方法适当地说明了信息群的大小，并且通常比现有的方法，尤其是在可忽略的群集大小下设计的方法。使用对酒精使用和牙周研究的纵向研究的数据来说明该方法的应用。
In clustered data setting, informative cluster size has been a focus of recent research. In the nonparametric context, the problem has been considered mainly for testing equality of distribution functions. The aim in this paper is to develop inferential procedure for the Wilcoxon-Mann-Whintey effect (also known as the nonprametric relative effect). Unbiased estimator is provided and its asymptotic properties are investigated. The asymptotic theory is employed to develop inferential methods. While the proposed method takes information in the cluster sizes into consideration when constructing the estimator, it is equally applicable for ignorable cluster size situation. Simulation results show that our method appropriately accounts for informative cluster size and it generally outperforms existing methods, especially those designed under ignorable cluster sizes. The applications of the method is illustrated using data from a longitudinal study of alcohol use and a periodontal study.
