Rank and pseudo-rank procedures for independent observations in factorial designs. Using R and SAS

DOI10.1007/978-3-030-02914-2zbMath1455.62001OpenAlexW2960131859MaRDI QIDQ2332339

Frank Konietschke, Edgar Brunner, Arne C. Bathke

Publication date: 4 November 2019

Published in: Springer Series in Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-02914-2

zbMATH Keywords

confidence intervalsempirical distributionordinal datanonparametric statisticsWilcoxon-Mann-Whitney testhypothesis testsrank transformKruskal-Wallis testdichotomous datadiscrete and continuous datafactorical designnonparametric effectpseudo-rank-based inference methodologypseudo-ranksrank-based inference methodologyreal data examples

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Software, source code, etc. for problems pertaining to statistics (62-04) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric tolerance and confidence regions (62G15) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics (62-01) Factorial statistical designs (62K15) Applications of statistics to psychology (62P15) Statistical aspects of big data and data science (62R07)

Related Items (5)

Testing for equality of distributions using the concept of (niche) overlap ⋮ Pseudo-Ranks: The Better Way of Ranking? ⋮ Ranks and Pseudo‐ranks—Surprising Results of Certain Rank Tests in Unbalanced Designs ⋮ The multi-aspect tests in the presence of ties ⋮ Simultaneous inference for Kendall's tau

Uses Software

• R
• SAS
• MIXED
• coin
• rankFD
• nparcomp
• clinfun
• NPAR1WAY
• PROC FREQ
• PROC TTEST
• PROC RANK
• PROC POWER

This page was built for publication: Rank and pseudo-rank procedures for independent observations in factorial designs. Using R and SAS