How to Address Non-normality: A Taxonomy of Approaches, Reviewed, and Illustrated.
How to Address Non-normality: A Taxonomy of Approaches, Reviewed, and Illustrated.
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DOI：
10.3389/fpsyg.2018.02104
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发表时间：
2018
影响因子：
3.8
通讯作者：
Wong ACM
中科院分区：
文献类型：
--
作者：
Pek J;Wong O;Wong ACM
线性模型通常作为在心理学中应用统计学的起点。通常，超出线性模型的正规培训是有限的，由于数据非正态性的普遍存在，造成了潜在的教学差距。我们回顾了61个最近出版的本科和研究生教科书介绍统计和线性模型，专注于他们的治疗非正态性。本综述确定了至少八种不同的方法，建议解决非正态性，我们组织成一个新的分类方法：（a）保持在线性模型内，（B）改变数据，（c）将正态性视为信息或滋扰。由于教科书对这些方法的报道往往是粗略的，而介绍这些方法的方法学论文通常是非统计学家无法获得的，因此这篇综述被设计成一种快乐的媒介。我们提供了一个相对非技术性的先进的方法，可以解决非正态性（和异方差），从而为起点，以促进最佳实践中的线性模型的应用。我们还提出了三个实证的例子，以突出这些方法的动机和结果之间的区别。本文还回顾了当前状态的方法研究，在解决非正态线性建模框架内。预计我们的分类法将提供一个有用的概述和出发点的研究人员有兴趣扩展他们的知识，从线性模型的角度来解决非正态性的方法。
The linear model often serves as a starting point for applying statistics in psychology. Often, formal training beyond the linear model is limited, creating a potential pedagogical gap because of the pervasiveness of data non-normality. We reviewed 61 recently published undergraduate and graduate textbooks on introductory statistics and the linear model, focusing on their treatment of non-normality. This review identified at least eight distinct methods suggested to address non-normality, which we organize into a new taxonomy according to whether the approach: (a) remains within the linear model, (b) changes the data, and (c) treats normality as informative or as a nuisance. Because textbook coverage of these methods was often cursory, and methodological papers introducing these approaches are usually inaccessible to non-statisticians, this review is designed to be the happy medium. We provide a relatively non-technical review of advanced methods which can address non-normality (and heteroscedasticity), thereby serving a starting point to promote best practice in the application of the linear model. We also present three empirical examples to highlight distinctions between these methods' motivations and results. The paper also reviews the current state of methodological research in addressing non-normality within the linear modeling framework. It is anticipated that our taxonomy will provide a useful overview and starting place for researchers interested in extending their knowledge in approaches developed to address non-normality from the perspective of the linear model.
影响因子：
4.3
作者：
Baayen, Harald;Vasishth, Shravan;Bates, Douglas
通讯作者：
Bates, Douglas