rcompanion (version 2.3.26)

# cramerV: Cramer's V (phi)

## Description

Calculates Cramer's V for a table of nominal variables; confidence intervals by bootstrap.

## Usage

```cramerV(
x,
y = NULL,
ci = FALSE,
conf = 0.95,
type = "perc",
R = 1000,
histogram = FALSE,
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 `x` is a vector, `y` is 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 to `boot.ci`.

R

The number of replications to use for bootstrap.

histogram

If `TRUE`, produces a histogram of bootstrapped values.

digits

The number of significant digits in the output.

bias.correct

If `TRUE`, a bias correction is applied.

reportIncomplete

If `FALSE` (the default), `NA` will 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.

## References

http://rcompanion.org/handbook/H_10.html

`cohenW`

## Examples

Run this code
``````# NOT RUN {
### Example with table
data(Anderson)
fisher.test(Anderson)
cramerV(Anderson)

### Example with two vectors
Species = c(rep("Species1", 16), rep("Species2", 16))
Color   = c(rep(c("blue", "blue", "blue", "green"),4),
rep(c("green", "green", "green", "blue"),4))
fisher.test(Species, Color)
cramerV(Species, Color)

# }
``````

Run the code above in your browser using DataCamp Workspace