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Analysis of means: a generalized approach using R

机译:均值分析:使用R的广义方法

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Papers on the analysis of means (ANOM) have been circulating in the quality control literature for decades, routinely describing it as a statistical stand-alone concept. Therefore, we clarify that ANOM should rather be regarded as a special case of a much more universal approach known as multiple contrast tests (MCTs). Perceiving ANOM as a grand-mean-type MCT paves the way for implementing it in the open-source software R. We give a brief tutorial on how to exploit R's versatility and introduce the R package ANOM for drawing the familiar decision charts. Beyond that, we illustrate two practical aspects of data analysis with ANOM: firstly, we compare merits and drawbacks of ANOM-type MCTs and ANOVA F-test and assess their respective statistical powers, and secondly, we show that the benefit of using critical values from multivariate t-distributions for ANOM instead of simple Bonferroni quantiles is oftentimes negligible.
机译:关于均值分析(ANOM)的论文已经在质量控制文献中流传了数十年,通常将其描述为一个统计上的独立概念。因此,我们明确指出,应将ANOM视为一种更为通用的方法(称为多重对比测试(MCT))的特例。将ANOM理解为平均水平的MCT为在开源软件R中实现它铺平了道路。我们提供了有关如何利用R的多功能性的简短教程,并介绍了R软件包ANOM来绘制熟悉的决策图。除此之外,我们还说明了使用ANOM进行数据分析的两个实际方面:首先,我们比较了ANOM型MCT和ANOVA F检验的优缺点,并评估了它们各自的统计能力,其次,我们证明了使用临界值的好处通常,对于ANOM的多变量t分布而不是简单的Bonferroni分位数,可以忽略不计。

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