A studentized permutation test for the nonparametric Behrens-Fisher problem in paired data
A studentized permutation test for the nonparametric Behrens-Fisher problem in paired data
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DOI：
10.1214/12-ejs714
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发表时间：
2012-01-01
影响因子：
1.1
通讯作者：
Pauly, Markus
中科院分区：
文献类型：
--
作者：
Konietschke, Frank;Pauly, Markus
我们考虑匹配对的非参数排序方法，即使在无治疗效果的零假设下，其分布也可能具有不同的形状。虽然数据可能无法交换下的空值，我们调查的置换方法作为一个有效的程序有限的样本量。特别是，我们得到的学生化的置换分布下的替代品，它可以用于（1 -α）-置信区间的建设的限制。仿真研究表明，新的方法是更准确的比它的竞争对手。使用一个真实的数据集的程序进行说明。
We consider nonparametric ranking methods for matched pairs, whose distributions can have different shapes even under the null hypothesis of no treatment effect. Although the data may not be exchangeable under the null, we investigate a permutation approach as a valid procedure for finite sample sizes. In particular, we derive the limit of the studentized permutation distribution under alternatives, which can be used for the construction of (1 - alpha)-confidence intervals. Simulation studies show that the new approach is more accurate than its competitors. The procedures are illustrated using a real data set.