Completely Randomized Designs

Kenneth J. Berry and Janis E. Johnston

Chapter Chapter 6 in Statistical Methods: Connections, Equivalencies, and Relationships, 2023, pp 217-289 from Springer

Abstract: Abstract Chapter 6 describes connections, equivalencies, and relationships relating to multi-sample tests of null hypotheses. First, Fisher’s conventional one-way completely randomized analysis of variance is described. Second, a multi-sample permutation test is presented and the connection linking the two tests is established. An example analysis illustrates the differences in the two approaches and the connection linking the two tests. Third, measures of effect size for multiple independent samples are described and the interconnections among the measures of effect size are detailed. Fourth, the connection linking the analysis of variance and the intraclass correlation coefficient is described. Fifth, the Kruskal–Wallis g-sample rank-sum test is described and illustrated with a small rank-score dataset. A permutation alternative multi-sample rank-sum test is introduced and the connection linking the Kruskal–Wallis H test statistic and the permutation multi-sample test statistic is described and illustrated with an example analysis.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-41896-9_6

Ordering information: This item can be ordered from
http://www.springer.com/9783031418969

DOI: 10.1007/978-3-031-41896-9_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().