Lüpsen, Haiko (2018). Varianzanalysen - Prüfen der Voraussetzungen und nichtparametrische Methoden sowie praktische Anwendungen mit R und SPSS. Version 3.1. Technical Report.

[img]
Preview
PDF
nonpar-anova.pdf - Updated Version

Download (1MB) | Preview

Abstract

Die Voraussetzungen der parametrischen 1- und mehrfaktoriellen Varianzanalyse, mit und ohne Messwiederholungen, werden besprochen. Ferner werden eine Reihe von alternativen Verfahren vorgestellt, insbesondere einige nichtparametrische, darunter RT (rank transform), INT (inverse normal transform), ART (aligned rank transform), Puri & Sen (L statistic), van der Waerden und Akritas & Brunner (ATS anova type statistic), die sich auf die parametrische Varianzanalyse zurückführen lassen, sowie dichotome und ordinale logistische Regression, als auch generalized linear models (GEE und GLMM) als Verallgemeinerungen für gemischte Versuchspläne. Hierzu werden Lösungen mit R und SPSS ausführlich gezeigt.

Item Type: Preprints, Working Papers or Reports (Technical Report)
Translated title:
TitleLanguage
Analysis of Variance - Checking Assumptions and nonparametric Methods as well as Applications with R and SPSSEnglish
Translated abstract:
AbstractLanguage
The assumptions of the parametric one- and multifactorial anova, with and without repeated measurements, are discussed. A number of alternative procedures are presented, especially some nonparametric anovas, among others RT (rank transform), INT (inverse normal transform), ART (aligned rank transform), Puri & Sen (L statistic), van der Waerden and Akritas & Brunner (ATS anova type statistic), which can be reduced to the parametric anova, as well as the dichotomous and polychotomous logistic regression, also generalized linear models (GEE und GLMM) for mixed designs. Solutions with R and SPSS are offered and discussed.English
Creators:
CreatorsEmailORCIDORCID Put Code
Lüpsen, Haikoluepsen@uni-koeln.deUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-85429
Number of Pages: 235
Date: 10 August 2018
Language: German
Faculty: Faculty of Mathematics and Natural Sciences
Divisions: Faculty of Mathematics and Natural Sciences > Department of Mathematics and Computer Science > Institute of Computer Science
Subjects: Data processing Computer science
General statistics
Uncontrolled Keywords:
KeywordsLanguage
nichtparametrisch, Varianzanalyse, RegressionGerman
URI: http://kups.ub.uni-koeln.de/id/eprint/8542

Downloads

Downloads per month over past year

Export

Actions (login required)

View Item View Item