多响应的分组Hotelling’s T^2检验（英文）  

Group Hotelling’s T^2 Test for Comparing Multiple Endpoints

作　　者：张胜虎 张三国 李启寨[3] ZHANG Shenghu;ZHANG Sanguo;LI Qizhai(School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China;School of Mathematics and Information Science, Jiangxi Normal University, Nanchang, 330022, China;LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China)

机构地区：[1]中国科学院大学数学科学学院,北京100049 [2]江西师范大学数学与信息科学学院,南昌330022 [3]中国科学院数学与系统科学研究院,北京100190

出　　处：《应用概率统计》2019年第3期317-330,共14页Chinese Journal of Applied Probability and Statistics

基　　金：partly supported by the Beijing Natural Science Foundation(Grant No.2180006);the National Nature Science Foundation of China(Grant No.11722113)

摘　　要：两样本的多响应比较在实际中应用非常广泛.当样本不服从正态分布时,Hotelling’s T^2检验(HT)的功效普遍不高.为了解决这一问题,本文提出了分组Hotelling’s T^2检验(GHT),即对数据进行逆正态变换后,在每一组中进行HT,然后基于每组的p值构造统计量并取最大值.大量模拟表明,GHT比HT和其他已有检验更加稳健.最后,应用于血浆肾素活性和大脑衰老数据进一步验证GHT的有效性.Comparisons between two samples with multiple endpoints are often encountered in many real applications and Hotelling's T2 test (HT) may suffer from loss of efficiency when multi- variate normality assumption is violated. To overcome this issue,we propose a group Hotelling's T^2 test (GHT) where HT is conducted within each group after inverse normal transformation and then use the maximum value among combined statistics based on p-values at the group-level. Extensive simulations show that GHT is more robust than HT and some other existing procedures. Final- ly,the applications to plasma-renin activity in serum study and the ageing human brain further demonstrate the performance of GHT.

关 键 词：逆正态变换 多响应 秩 功效 

分 类 号：O212[理学—概率论与数理统计] Q348[理学—数学]