Robust Statistical Methods Using WRS2
Robust Statistical Methods Using WRS2
复制标题
使用 WRS2 的稳健统计方法
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
R. Wilcox
中科院分区：
文献类型：
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作者：
P. Mair;R. Wilcox
这一小插曲是Mair和Wilcox（2020）的（稍微）修改过的艾德版本，发表在行为研究方法上。它介绍了R包WRS 2，它实现了各种强大的统计方法。它通过介绍稳健的位置、离散度和相关性度量来阐述稳健统计的基础。然后，位置和离散度测量用于独立和相关样本t检验和ANOVA的稳健变量，包括受试者内间设计和分位数ANOVA。此外，鲁棒ANCOVA以及鲁棒的调解模型。这篇论文的目标是应用研究人员;因此，它是相当非技术性的，并以教程的风格撰写。特别强调在社会和行为科学中的应用，并说明如何在R中执行相应的鲁棒分析。补充资料中给出了再现文中结果的R码。
This vignette is a (slightly) modified version of Mair and Wilcox (2020), published in Behavior Research Methods. It introduces the R package WRS2 that implements various robust statistical methods. It elaborates on the basics of robust statistics by introducing robust location, dispersion, and correlation measures. The location and dispersion measures are then used in robust variants of independent and dependent samples t -tests and ANOVA, including between-within subject designs and quantile ANOVA. Further, robust ANCOVA as well as robust mediation models are introduced. The paper targets applied researchers; it is therefore kept rather non-technical and written in a tutorial style. Special emphasis is placed on applications in the social and behavioral sciences and illustrations of how to perform corresponding robust analyses in R. The R code for reproducing the results in the paper is given in the supplementary materials.