Correlation and Association

Kenneth J. Berry (), Kenneth L. Kvamme, Janis E. Johnston and Paul W. Mielke, Jr.
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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 10 in Permutation Statistical Methods with R, 2021, pp 499-590 from Springer

Abstract: Abstract In this chapter presents exact and Monte Carlo permutation statistical methods for measures of linear correlation and association. Also presented in this chapter is a permutation-based measure of effect size for a variety of measures of correlation and association. Simple linear correlation between two variables constitutes the foundation for a large family of advanced analytic techniques and is taught in every introductory course. In addition, this chapter presents a number of non-parametric measures of correlation and association with permutation alternatives, including Spearman’s rank-order correlation coefficient, Kendall’s $$\tau _{a}$$ τ a and $$\tau _{b}$$ τ b measures of ordinal association, and Spearman’s footrule measure of disarray.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-74361-1_10

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DOI: 10.1007/978-3-030-74361-1_10

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