A Regression Framework for Rank Tests Based on the Probabilistic Index Model

• 成果类型: Article
• 署名作者: De Neve, Jan; Thas, Olivier
• 署名单位: Ghent University; University of Wollongong
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2015.1016226
• 发表日期: 2015
• 页码: 1276-1283
• 关键词: nonparametric hypotheses; statistics

摘要

We demonstrate how many classical rank tests, such as the Wilcoxon Mann Whitney, Kruskal Wallis, and Friedman test, can be embedded in a statistical modeling framework and how the method can be used to construct new rank tests. In addition to hypothesis testing, the method allows for estimating effect sizes with an informative interpretation, resulting in a better understanding of the data. Supplementary materials for this article are available online.