Contingency Tables

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

Chapter Chapter 11 in A Primer of Permutation Statistical Methods, 2019, pp 409-459 from Springer

Abstract: Abstract This chapter introduces permutation methods for the analysis of contingency tables. Included in this chapter are six example analyses illustrating computation of permutation methods for goodness-of-fit tests, analysis of contingency tables composed of two nominal-level (categorical) variables, analysis of contingency tables composed of two ordinal-level (ranked) variables, analysis of contingency tables composed of one nominal-level variable and one ordinal-level variable, analysis of contingency tables composed of one nominal-level variable and one interval-level variable, and analysis of contingency tables composed of one ordinal-level variable and one interval-level variable. Included in this chapter are permutation versions of Pearson chi-squared goodness-of-fit test, Pearson’s chi-squared test of independence, Cramér’s symmetrical measure of nominal association, Goodman and Kruskal’s τ a and τ b asymmetric measures of association for two categorical variables, Goodman and Kruskal’s G measure of association for two ranked variables, Somers’ d yx and d xy asymmetric measures of association for two ranked variables, Freeman’s θ measure of association for a categorical independent variable and a ranked dependent variable, Pearson’s point-biserial correlation coefficient for one dichotomous variable and one interval-level variable, and Jaspen’s correlation coefficient for one ranked variable and one interval-level variable.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-20933-9_11

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DOI: 10.1007/978-3-030-20933-9_11

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