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EBOOK
Author Brunner, Edgar, 1943- http://id.loc.gov/vocabulary/relators/aut.
Title Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs : Using R and SAS / by Edgar Brunner, Arne C. Bathke, Frank Konietschke.
Imprint Cham : Springer International Publishing : Imprint: Springer, 2018.
Edition First edition 2018.

LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
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LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
Author Brunner, Edgar, 1943- http://id.loc.gov/vocabulary/relators/aut.
Series Springer Series in Statistics, 0172-7397.
Springer series in statistics. 0172-7397.
Subject Statistics.
Pharmaceutical technology.
Mathematical statistics.
Alt Name Bathke, Arne C., http://id.loc.gov/vocabulary/relators/aut.
Konietschke, Frank, http://id.loc.gov/vocabulary/relators/aut.
Description 1 online resource (XX, 521 pages 30 illustrations, 4 illustrations in color.) : online resource.
Edition First edition 2018.
Contents 1 Types of Data and Designs -- 2 Distributions and Effects -- 3 Two Samples -- 4 Several Samples -- 5 Two-Factor Crossed Designs -- 6 Designs with Three and More Factors -- 7 Derivation of Main Results -- 8 Mathematical Techniques -- References -- A Software and Program Code -- B Data Sets and Descriptions -- Index.
Summary 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. .
Bibliography Note Includes bibliographical references and index.
ISBN 9783030029142
303002914X
9783030029128 print
ISBN/ISSN 10.1007/978-3-030-02914-2
10.1007/978-3-030-02
OCLC # 1117328872
Additional Format Printed edition: 9783030029128.
Printed edition: 9783030029135.


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