Brunner, Edgar; Bathke, Arne C.; Konietschke, Frank Rank and pseudo-rank procedures for independent observations in factorial designs. Using R and SAS. (English) Zbl 1455.62001 Springer Series in Statistics. Cham: Springer (ISBN 978-3-030-02912-8/hbk; 978-3-030-02914-2/ebook). xx, 521 p. (2019). From the cover of the book: “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.” The book is very large structured in the Preface, 8 chapters (divided in 57 subchapters), Appendix A (Software and program code), Appendix B (Data sets and descriptions), Appendix C (Correction), Acknowledgments, References, Index: Chapter 1. Types of data and designs – Chapter 2. Distributions and effects – Chapter 3. Two samples – Chapter 4. Several samples – Chapter 5. Two-factor crossed designs – Chapter 6. Designs with three and more factors – Chapter 7. Derivation of main results – Chapter 8. Mathematical techniques. Most of the chapters finish with a subchapter “Exercises and problems” and some subchapters finish with a summary, thus we have more than 110 problems for solving. The bibliography contains more than 250 references and the index more than 900 items. The book can be very recommended all readers who are interested in this field. Reviewer: Ludwig Paditz (Dresden) Cited in 1 ReviewCited in 5 Documents MSC: 62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics 62R07 Statistical aspects of big data and data science 62G10 Nonparametric hypothesis testing 62G15 Nonparametric tolerance and confidence regions 62G20 Asymptotic properties of nonparametric inference 62K15 Factorial statistical designs 62P10 Applications of statistics to biology and medical sciences; meta analysis 62P15 Applications of statistics to psychology 62-04 Software, source code, etc. for problems pertaining to statistics Keywords:discrete and continuous data; ordinal data; dichotomous data; factorical design; pseudo-ranks; rank transform; nonparametric effect; nonparametric statistics; hypothesis tests; Kruskal-Wallis test; Wilcoxon-Mann-Whitney test; confidence intervals; empirical distribution; real data examples; rank-based inference methodology; pseudo-rank-based inference methodology Software:clinfun; NPAR1WAY; PROC RANK; PROC FREQ; rankFD; PROC TTEST; nparcomp; PROC POWER; R; coin; SAS; MIXED PDFBibTeX XMLCite \textit{E. Brunner} et al., Rank and pseudo-rank procedures for independent observations in factorial designs. Using R and SAS. Cham: Springer (2019; Zbl 1455.62001) Full Text: DOI