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Distribution-free two-sample comparisons in the case of heterogeneous variances

机译:异质方差情况下的无分布两样本比较

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摘要

Behavioral ecologists are often faced with a situation where they need to compare the central tendencies of two samples. The standard tools of the t test and Mann-Whitney U test (equivalent to the Wilcoxon rank-sum test) are unreliable when the variances of the groups are different. The problem is particularly severe when sample sizes are different between groups. The unequal-variance t test (Welch test) may not be suitable for nonnormal data. Here, we propose the use of Brunner and Munzel's generalized Wilcoxon test followed by randomization to allow for small sample sizes. This tests whether the probability of an individual from one population being bigger than an individual from the other deviates from random expectation. This probability may sometimes be a more clear and informative measure of difference between the groups than a difference in more commonly used measures of central tendency (such as the mean). We provide a recipe for carrying out a statistical test of the null hypothesis thatthis probability is 50% and demonstrate the effectiveness of this technique for sample sizes typical in behavioral ecology. Although the test is not available in any commercial software package, it is relatively straightforward to implement for anyone with some programming ability. Furthermore, implementations in R and SAS are freely available on the internet.
机译:行为生态学家经常面临需要比较两个样本的中心趋势的情况。当组的方差不同时,t检验和Mann-Whitney U检验(相当于Wilcoxon秩和检验)的标准工具不可靠。当组之间的样本大小不同时,该问题尤其严重。方差t检验(韦尔奇检验)可能不适用于非正常数据。在这里,我们建议使用Brunner和Munzel的广义Wilcoxon检验,然后进行随机化以允许小样本量。这测试了来自一个总体的个体大于另一个总体的个体的概率是否偏离随机期望。有时,这种概率可能是组间差异的一种更清晰,更有意义的度量,而不是更常用的集中趋势度量(例如均值)的差异。我们提供了对概率为50%的原假设进行统计检验的方法,并证明了该技术对于行为生态学中典型样本量的有效性。尽管该测试在任何商业软件包中均不可用,但对于具有一定编程能力的任何人来说,实施该测试都相对简单。此外,R和SAS的实现可在互联网上免费获得。

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