Calculate the Cramer's V measure of association
cramersV(...)Arguments to be passed to the chisq.test function.
A numeric variable with a single element corresponding to the value of V.
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.
# Consider an experiment with two conditions, each with 100
# 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)
#> condition1 condition2
#> choice1 30 35
#> choice2 20 30
#> choice3 50 35
# 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)
#>
#> Pearson's Chi-squared test
#>
#> data: X
#> X-squared = 5.0317, df = 2, p-value = 0.0808
#>
# To estimate the effect size we can use Cramer's V:
cramersV( X ) # returns a value of 0.159
#> [1] 0.1586139