A studentized permutation test for the non-parametric Behrens–Fisher problem

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• 作者：Karin Neubert ; Edgar Brunner
• 关键词：Studentized statistic ; Asymptotic distribution ; Brunner– ; Munzel test ; Ordered categorical data ; Rank test ; Count data
• 刊名：Computational Statistics and Data Analysis
• 出版年：2007
• 出版时间：15 June 2007
• 年：2007
• 卷：51
• 期：10
• 页码：5192-5204
• 全文大小：286 K

文摘

For the non-parametric Behrens–Fisher problem a permutation test based on the studentized rank statistic of Brunner and Munzel is proposed. This procedure is applicable to count or ordered categorical data. By applying the central limit theorem of Janssen, it is shown that the asymptotic permutational distribution of this test statistic is a standard normal distribution. For very small and very different sample sizes, frequently occurring in medical and biological applications, an extensive simulation study suggests that this permutation test works well for data from several underlying distributions. The proposed test is applied to data from a clinical trial.