LEADER 03856nam  22006255  450 
001 9910332461203321
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010   $a3-030-02914-X
024 7 $a10.1007/978-3-030-02914-2
035   $a(CKB)4100000008707648
035   $a(MiAaPQ)EBC5830016
035   $a(DE-He213)978-3-030-02914-2
035   $a(PPN)238488845
035   $a(EXLCZ)994100000008707648
100   $a20190715d2018      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aRank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs $eUsing R and SAS /$fby Edgar Brunner, Arne C. Bathke, Frank Konietschke
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (535 pages)
225 1 $aSpringer Series in Statistics,$x0172-7397
311   $a3-030-02912-3 
320   $aIncludes bibliographical references and index.
327   $a1 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. .
330   $aThis book explains how to analyze independent data from factorial designs without having to make restrictive assumptions, such as normality of the data, or equal variances. The general approach also allows for ordinal and even dichotomous data. The underlying effect size is the nonparametric relative effect, which has a simple and intuitive probability interpretation. The data analysis is presented as comprehensively as possible, including appropriate descriptive statistics which follow a nonparametric paradigm, as well as corresponding inferential methods using hypothesis tests and confidence intervals based on pseudo-ranks. Offering clear explanations, an overview of the modern rank- and pseudo-rank-based inference methodology and numerous illustrations with real data examples, as well as the necessary R/SAS code to run the statistical analyses, this book is a valuable resource for statisticians and practitioners alike. .
410  0$aSpringer Series in Statistics,$x0172-7397
606   $aStatistics 
606   $aBiostatistics
606   $aPharmaceutical technology
606   $aR (Computer program language)
606   $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030
606   $aBiostatistics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15020
606   $aPharmaceutical Sciences/Technology$3https://scigraph.springernature.com/ontologies/product-market-codes/B21010
606   $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001
615  0$aStatistics .
615  0$aBiostatistics.
615  0$aPharmaceutical technology.
615  0$aR (Computer program language).
615 14$aStatistics for Life Sciences, Medicine, Health Sciences.
615 24$aBiostatistics.
615 24$aPharmaceutical Sciences/Technology.
615 24$aStatistical Theory and Methods.
676   $a610.727
676   $a519.5
700   $aBrunner$b Edgar$4aut$4http://id.loc.gov/vocabulary/relators/aut$0768327
702   $aBathke$b Arne C$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aKonietschke$b Frank$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910332461203321
996   $aRank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs$91923077
997   $aUNINA