
Cramer's V (phi)
cramerV.RdCalculates Cramer's V for a table of nominal variables; confidence intervals by bootstrap. Function taken from the rcompanion Rpackage.
Usage
cramerV(
x,
y = NULL,
ci = FALSE,
conf = 0.95,
type = "perc",
R = 1000,
digits = 4,
bias.correct = FALSE,
reportIncomplete = FALSE,
verbose = FALSE,
...
)Arguments
- x
Either a two-way table or a two-way matrix. Can also be a vector of observations for one dimension of a two-way table.
- y
If
xis a vector,yis the vector of observations for the second dimension of a two-way table.- ci
If
TRUE, returns confidence intervals by bootstrap. May be slow.- conf
The level for the confidence interval.
- type
The type of confidence interval to use. Can be any of "
norm", "basic", "perc", or "bca". Passed toboot.ci.- R
The number of replications to use for bootstrap.
- digits
The number of significant digits in the output.
- bias.correct
If
TRUE, a bias correction is applied.- reportIncomplete
If
FALSE(the default),NAwill be reported in cases where there are instances of the calculation of the statistic failing during the bootstrap procedure.- verbose
If
TRUE, prints additional statistics.- ...
Additional arguments passed to
chisq.test.
Value
A single statistic, Cramer's V. Or a small data frame consisting of Cramer's V, and the lower and upper confidence limits.
Details
Cramer's V is used as a measure of association between two nominal variables, or as an effect size for a chi-square test of association. For a 2 x 2 table, the absolute value of the phi statistic is the same as Cramer's V.
Because V is always positive, if type="perc",
the confidence interval will
never cross zero. In this case,
the confidence interval range should not
be used for statistical inference.
However, if type="norm", the confidence interval
may cross zero.
When V is close to 0 or very large, or with small counts, the confidence intervals determined by this method may not be reliable, or the procedure may fail.
Author
Salvatore Mangiafico, mangiafico@njaes.rutgers.edu