rstatix (version 0.7.2)

friedman_test: Friedman Rank Sum Test

Description

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(). Read more: Friedman test in R.

Usage

friedman_test(data, formula, ...)

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.

Arguments

data

a data.frame containing the variables in the formula.

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.

Examples

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

# Friedman rank sum test
#:::::::::::::::::::::::::::::::::::::::::
df %>% friedman_test(len ~ dose | id)