A Two-Sample Cluster-adjusted Rank-based Test for Multiple Endpoints

主讲人:Prof. Aiyi Liu(National Institute of Child Health and Human Development, National Institutes of Health)
时间:2017年10月17日下午3:30   地点:N205

【摘要】Multiple endpoints are often naturally clustered based on their scienti c functions. Tests that compare these clustered outcomes between independent groups may lose eciency if the cluster structures are not properly accounted for. We propose a cluster-adjusted multivariate test procedure for the comparison and demonstrate its gain of eciency over a number of popular test procedures that ignore the clusters. Data from a dietary intervention trial and a case-control study on neural tube defects are used to exemplify the methods