Permutation tests for mixed paired and two-sample designs

被引：0
|
作者：
E. N. Johnson
S. J. Richter
机构：
[1] Wake Forest School of Medicine,
[2] University of North Carolina at Greensboro,undefined
来源：
Computational Statistics | 2022年 / 37卷
关键词：
Paired design; Missing data; Permutation test; Ranks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Permutation tests based on previously developed statistics are proposed for the case of mixed paired and two-sample designs. Different weighting schemes of previous tests are explored to understand the strengths and weaknesses of each test. A simulation study compares the power and Type I error rates of the new tests with those previously developed. Rank-based statistics generally performed as well as or better than parametric statistics, particularly for nonnormal distributions.
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收藏
页码：739 / 750
页数：11
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