Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs
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 u
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Edgar Brunner Arne C. Bathke Frank Konietschke
Rank and PseudoRank Procedures for Independent Observations in Factorial Designs Using R and SAS
Springer Series in Statistics Advisors: P. Diggle, U. Gather, S. Zeger
More information about this series at http://www.springer.com/series/692
Edgar Brunner • Arne C. Bathke • Frank Konietschke
Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs Using R and SAS
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Edgar Brunner Department of Medical Statistics University of G¨ottingen University Medical Center G¨ottingen, Germany
Arne C. Bathke Department of Mathematics University of Salzburg Salzburg, Austria
Frank Konietschke Treuchtlinger Straße 4 10779 Berlin
SAS is a registered trademark of SAS Institute. ISSN 0172-7397 ISSN 2197-568X (electronic) Springer Series in Statistics ISBN 978-3-030-02912-8 ISBN 978-3-030-02914-2 (eBook) https://doi.org/10.1007/978-3-030-02914-2 Mathematics Subject Classification (2010): 62G10, 62G15, 62G20, 62P10, 62P15 © Springer Nature Switzerland AG 2018 Partly based on a translation from the German language edition: Nichtparametrische Datenanalyse by Edgar Brunner and Ullrich Munzel, © Springer-Verlag Berlin Heidelberg 2013. All Rights Reserved This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
This is a book on modern nonparametric statistics for factorial designs, using ranks and pseudo-ranks. The field of nonparametric statistics may be most easily described by first introducing its counterpart, parametric statistics. Parametric statistics is concerned with modeling, representing, and analyzing data assumed to originate from known parameterized classes of distributions, for example from normal, exponential, o
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