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Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs = Using R and SAS /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs / by Edgar Brunner, Arne C. Bathke, Frank Konietschke.
Reminder of title:	Using R and SAS /
Author:	Brunner, Edgar.
other author:	Bathke, Arne C.
Description:	XX, 521 p. 30 illus., 4 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-3-030-02914-2
ISBN:	9783030029142

Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs = Using R and SAS /
Brunner, Edgar.

Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs Using R and SAS /[electronic resource] :by Edgar Brunner, Arne C. Bathke, Frank Konietschke. - 1st ed. 2018. - XX, 521 p. 30 illus., 4 illus. in color.online resource. - Springer Series in Statistics,0172-7397. - Springer Series in Statistics,.

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. .

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. .

ISBN: 9783030029142

Standard No.: 10.1007/978-3-030-02914-2doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs = Using R and SAS /
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