Two-Sample Tests

Kenneth J. Berry, Janis E. Johnston and Paul W. Mielke
Additional contact information
Kenneth J. Berry: Colorado State University, Department of Sociology
Janis E. Johnston: Alexandria
Paul W. Mielke: Colorado State University, Department of Statistics

Chapter Chapter 6 in A Primer of Permutation Statistical Methods, 2019, pp 153-205 from Springer

Abstract: Abstract This chapter introduces permutation methods for two-sample tests. Included in this chapter are six example analyses illustrating computation of exact permutation probability values for two-sample tests, calculation of measures of effect size for two-sample tests, the effect of extreme values on conventional and permutation two-sample tests, exact and Monte Carlo permutation procedures for two-sample tests, application of permutation methods to two-sample rank-score data, and analysis of two-sample multivariate data. Included in this chapter are permutation versions of Student’s two-sample t test, the Wilcoxon–Mann–Whitney two-sample rank-sum test, Hotelling’s multivariate T 2 test for two independent samples, and a permutation-based alternative for the four conventional measures of effect size for two-sample tests: Cohen’s d ̂ $$\hat{d}$$ , Pearson’s r 2, Kelley’s 𝜖 2, and Hays’ ω ̂ 2 $$\hat{\omega }^{2}$$ .

Date: 2019
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:978-3-030-20933-9_6

Ordering information: This item can be ordered from
http://www.springer.com/9783030209339

DOI: 10.1007/978-3-030-20933-9_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 ().