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The use of nonparametric contrasts in one-way layouts and random block designs

机译:在单向布局和随机块设计中使用非参数对比

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Nonparametric simple-contrast estimates for one-way layouts based on Hodges-Lehmann estimators for two samples and confidence intervals for all contrasts involving only two treatments are found in the literature. Tests for such contrasts are performed from the distribution of the maximum of the rank sum between two treatments. For random block designs, simple contrast estimates based on Hodges-Lehmann estimators for one sample are presented. However, discussions concerning the significance levels of more complex contrast tests in nonparametric statistics are not well outlined. This work aims at presenting a methodology to obtain p-values for any contrast types based on the construction of the permutations required by each design model using a C-language program for each design type. For small samples, all possible treatment configurations are performed in order to obtain the desired p-value. For large samples, a fixed number of random configurations are used. The program prompts the input of contrast coefficients, but does not assume the existence or orthogonality among them. In orthogonal contrasts, the decomposition of the value of the suitable statistic for each case is performed and it is observed that the same procedure used in the parametric analysis of variance can be applied in the nonparametric case, that is, each of the orthogonal contrasts has a has a χ~2 distribution with one degree of freedom. Also, the similarities between the p-values obtained for nonparametric contrasts and those obtained through approximations suggested in the literature are discussed.
机译:在文献中发现了基于Hodges-Lehmann估计量的两个样本的单向布局的非参数简单对比估计,以及仅涉及两种处理的所有对比的置信区间。从两种处理之间的秩和最大值的分布中进行这种对比的测试。对于随机块设计,提出了一种基于Hodges-Lehmann估计量的简单对比度估计量。但是,关于非参数统计中更复杂的对比检验的显着性水平的讨论并未得到很好的概述。这项工作旨在提出一种方法,该方法基于每种设计模型使用C语言程序针对每种设计模型所需的排列构造,来获取任何对比度类型的p值。对于小样本,执行所有可能的处理配置以获得所需的p值。对于大样本,使用固定数量的随机配置。该程序提示输入对比度系数,但不假定它们之间存在或正交。在正交对比中,针对每种情况执行适当统计量的值分解,并且可以观察到,在非参数情况下可以应用在方差的参数分析中使用的相同过程,也就是说,每个正交对比都具有a具有一个自由度的χ〜2分布。此外,还讨论了通过非参数对比获得的p值与通过文献中提出的近似值获得的p值之间的相似性。

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