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Using orthogonal trend contrasts for testing ranked data with ordered alternatives

机译:使用正交趋势对比测试有序替代项的排名数据

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In the analysis of variance (ANOVA) the use of orthogonal contrasts is quite common and is a traditional topic in many basic ANOVA courses. Similar ideas apply to rank tests. In this paper we present a simple and general method that allows an orthogonal contrast decomposition of rank test statistics such as the Kruskal-Wallis, Friedman and Durbin statistics. The components of the test statistics are informative, particularly when ordered alternatives are of interest. The method can handle ties, and null distributions are readily available. Most of the methods are not new, but the way we present them is. Moreover, our formulation makes it easier to better understand and interpret the tests when the traditional location-shift assumption does not hold. The methods are illustrated using several data sets.
机译:在方差分析(ANOVA)中,正交对比的使用非常普遍,并且是许多基础ANOVA课程中的传统主题。类似的想法适用于等级测试。在本文中,我们提出了一种简单而通用的方法,该方法允许对秩检验统计量(例如Kruskal-Wallis,Friedman和Durbin统计量)进行正交对比分解。测试统计信息的组成部分内容丰富,尤其是在有序的替代方法引起关注时。该方法可以处理关系,并且空分布很容易获得。大多数方法不是新方法,但是我们介绍它们的方式是新方法。此外,在传统的位置偏移假设不成立的情况下,我们的公式可以更轻松地更好地理解和解释测试。使用几个数据集说明了这些方法。

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