Hamada Chikuma
Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, 6-3-1 Niijuku, Katsushika-ku, Tokyo 125-8585, Japan.
J Toxicol Pathol. 2018 Jan;31(1):15-22. doi: 10.1293/tox.2017-0050. Epub 2017 Sep 15.
Generally, multiple statistical analysis methods can be applied for certain kind of data, and conclusion could differ, depending on the selected statistical method. Therefore, it is necessary to fully understand the performance of each statistical method and to examine which method is appropriate to use and to standardize statistical methods for toxicity studies to be carried out routinely. Several viewpoints for selecting appropriate statistical methods are discussed in this review paper. According to the distribution form, i.e., whether a distribution has a bell shape without outliers or not, either a parametric or a nonparametric approach should be selected. The nonparametric approach is also available for categorical data. Depending on the design and purpose of a study, several forms of statistical analysis are available. Assuming dose dependency, comparisons with a control are conducted by Williams test (nonparametric: Shirley-Williams test). When a dose dependent relationship is not expected, comparisons with the control are conducted by Dunnett test (nonparametric: Steel test). All possible pairwise comparisons among groups are conducted by Tukey test (nonparametric: Steel-Dwass test). If we are interested in several specific comparisons among groups, the Bonferroni-adjusted Student's -test (nonparametric: the Bonferroni-adjusted Wilcoxon test) can be used.
一般来说，对于某类数据可以应用多种统计分析方法，并且结论可能会有所不同，这取决于所选择的统计方法。因此，有必要充分了解每种统计方法的性能，检查哪种方法适合使用，并规范常规进行的毒性研究的统计方法。本文讨论了选择合适统计方法的几个观点。根据分布形式，即分布是否具有无异常值的钟形，应选择参数法或非参数法。非参数法也适用于分类数据。根据研究的设计和目的，有几种形式的统计分析方法可供使用。假设存在剂量依赖性，与对照组的比较通过威廉姆斯检验（非参数：雪莉 - 威廉姆斯检验）进行。当预期不存在剂量依赖关系时，与对照组的比较通过邓尼特检验（非参数：斯蒂尔检验）进行。组间所有可能的两两比较通过图基检验（非参数：斯蒂尔 - 德瓦斯检验）进行。如果我们对组间的几个特定比较感兴趣，可以使用邦费罗尼校正的学生 t 检验（非参数：邦费罗尼校正的威尔科克森检验）。
