Provides a pipe-friendly framework to perform a Friedman rank sum test, which is the non-parametric alternative to the one-way repeated measures ANOVA test. Wrapper around the function friedman.test().

friedman_test(data, formula, ...)

## Arguments

data a data.frame containing the variables in the formula. a formula of the form a ~ b | c, where a (numeric) is the dependent variable name; b is the within-subjects factor variables; and c (factor) is the column name containing individuals/subjects identifier. Should be unique per individual. other arguments to be passed to the function friedman.test.

## Value

return a data frame with the following columns:

• .y.: the y (dependent) variable used in the test.

• n: sample count.

• statistic: the value of Friedman's chi-squared statistic, used to compute the p-value.

• p: p-value.

• method: the statistical test used to compare groups.

## Examples

# Load data
#:::::::::::::::::::::::::::::::::::::::
data("ToothGrowth")
df <- ToothGrowth %>%
filter(supp == "VC") %>%
mutate(id = rep(1:10, 3))