NONPARAMETRIC REPEATED SIGNIFICANCE TESTS FOR SOME ANALYSIS OF COVARIANCE MODELS

被引:1
作者
SEN, PK
机构
[1] Department of Biostatistics, University of North Carolina, Chapel Hill
来源
COMMUNICATIONS IN STATISTICS PART A-THEORY AND METHODS | 1979年 / 8卷 / 08期
关键词
analysis of covariance asymptotic effi-; ciency censoring Gaussian functions nonparametric tests repeated significance testing weak convergence;
D O I
10.1080/03610927908827801
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
For a general class of nonparametric analysis of covariance problems (with stochastic covariates), some repeated significance testing procedures are developed. These procedures rest on the construction of suitable rank order statistics based on the partial sequence of sample sizes and allow for a monitoring of experimentation with the objective of a possible early termination of experimentation. The basic theory is based on the weak convergence of certain stochastic processes relating to the rank order statistics. Various properties of the proposed tests are discussed. © 1979, Taylor & Francis Group, LLC. All rights reserved.
引用
收藏
页码:819 / 841
页数:23
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