Cramer's V

Calculate the Cramer's V measure of association

Arguments to be passed to the chisq.test function.

Calculates the Cramer's V measure of effect size for chi-square tests of association and goodness of fit. The arguments to the cramersV function are all passed straight to the chisq.test function, and should have the same format.



This package is under development, and has been released only due to teaching constraints. Until this notice disappears from the help files, you should assume that everything in the package is subject to change. Backwards compatibility is NOT guaranteed. Functions may be deleted in future versions and new syntax may be inconsistent with earlier versions. For the moment at least, this package should be treated with extreme caution.

See Also

chisq.test, assocstats (in the vcd package)

  • cramersV
library(lsr) # participants. Each participant chooses between one of three # options. Possible data for this experiment: condition1 <- c(30, 20, 50) condition2 <- c(35, 30, 35) X <- cbind( condition1, condition2 ) rownames(X) <- c( 'choice1', 'choice2', 'choice3' ) print(X) # To test the null hypothesis that the distribution of choices # is identical in the two conditions, we would run a chi-square # test: chisq.test(X) # To estimate the effect size we can use Cramer's V: cramersV( X ) # returns a value of 0.159
Documentation reproduced from package lsr, version 0.5, License: GPL-3

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