Chi-Squared and Related Measures

Kenneth J. Berry (), Kenneth L. Kvamme, Janis E. Johnston and Paul W. Mielke, Jr.
Additional contact information
Kenneth J. Berry: Colorado State University, Department of Sociology
Kenneth L. Kvamme: University of Arkansas, Department of Anthropology
Paul W. Mielke, Jr.: Deceased

Chapter Chapter 11 in Permutation Statistical Methods with R, 2021, pp 591-645 from Springer

Abstract: Abstract In this chapter introduces exact and Monte Carlo permutation statistical methods for Pearson’sPearson, K. Pearson, K. chi-squared goodness-of-fit test, Wilks’Wilks, S.S. Wilks, S.S. likelihood-ratio goodness-of-fit test, and Pearson’s chi-squared test of independence, along with selected measures of effect size based on the chi-squared test statistic and the likelihood-ratio test statistic.

Date: 2021
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:978-3-030-74361-1_11

Ordering information: This item can be ordered from
http://www.springer.com/9783030743611

DOI: 10.1007/978-3-030-74361-1_11

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 ().