Brunner E. Bathke A.C., Konietschke F. Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs: Using R and SAS

Springer, 2018. — 535 p. — (Springer Series in Statistics). — ISBN: 978-3-030-02912-8.This book explains how to analyze independent data from factorial designs without having to make restrictive assumptions, such as normality of the data, or equal variances. The general approach also allows for ordinal and even dichotomous data. The underlying effect size is the nonparametric relative effect, which has a simple and intuitive probability interpretation. The data analysis is presented as comprehensively as possible, including appropriate descriptive statistics which follow a nonparametric paradigm, as well as corresponding inferential methods using hypothesis tests and confidence intervals based on pseudo-ranks.
Offering clear explanations, an overview of the modern rank- and pseudo-rank-based inference methodology and numerous illustrations with real data examples, as well as the necessary R/SAS code to run the statistical analyses, this book is a valuable resource for statisticians and practitioners alike.Types of Data and Designs
Distributions and Effects
Two Samples
Several Samples
Two-Factor Crossed Designs
Designs with Three and More Factors
Derivation of Main Results
Mathematical Techniques
Correction to: Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs