Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs , 1st ed. 2018
Using R and SAS

Springer Series in Statistics Series

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Language: English

126.59 €

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521 p. · 15.5x23.5 cm · Hardback

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. 

 


Edgar Brunner is Professor Emeritus at the University of Göttingen, Germany and Visiting Professor at the University of Salzburg, Austria. In Göttingen, he was the Head of the Department of Medical Statistics from 1976 to 2009 and lectured at the Medical and Mathematics Faculties. Prof. Brunner has published numerous papers in high-quality journals, and has taught and given invited lectures on four continents. His research areas include rank methods; simultaneous confidence intervals; high-dimensional repeated measures; statistical methodology; and the application of rank methods for the analysis of diagnostic trials. Prof. Brunner has also collaborated with numerous authors from various countries and is honorary member of the German Region board of the International Biometric Society (IBS-DR). From 2004 to 2008, he was editor of the Biometrical Journal, and he was associate editor of JSPI from 2000 to 2011. Since 2009, he has been associate editor of the Biometrical Journal. 

Arne C. Bathke is a Professor of Statistics at the Department of Mathematics of the University of Salzburg, Austria. Previously, he was Director of Graduate Studies at the Department of Statistics and Director of the Applied Statistics Laboratory at the University of Kentucky, USA. Prof. Bathke has taught courses and given invited lectures on five continents. His methodological research is mainly in the areas of nonparametric statistics and multivariate inference. Furthermore, he has collaborated with subject matter scientists from a wide range of fields. He has received university-wide teaching awards from the University of Kentucky: the Provost's Award for outstanding teaching (2007) and the Alumni Association Great Teacher Award (2012). He was also named “Henry Clay Ambassador” by the Mayor of Lexington (KY) for his civil engagement, and he was commissioned “Kentucky Admiral” by the Secretary of the Kentucky Energy and Environment Cabinet. He

Offers a detailed overview of the modern rank- and pseudo-rank-based inference methodology

Richly illustrated with examples

Provides codes (R, SAS) for the statististical analysis

Includes supplementary material: sn.pub/extras