Provides a pipe-friendly framework to perform Kruskal-Wallis
rank sum test. Wrapper around the function
kruskal.test().
kruskal_test(data, formula, ...)a data.frame containing the variables in the formula.
a formula of the form x ~ group where x is a
numeric variable giving the data values and group is a factor with
one or multiple levels giving the corresponding groups. For example,
formula = TP53 ~ cancer_group.
other arguments to be passed to the function
kruskal.test.
return a data frame with the following columns:
.y.: the y variable used in the test.
n: sample count.
statistic: the kruskal-wallis rank sum statistic used to
compute the p-value.
p: p-value.
method: the
statistical test used to compare groups.
# Load data
#:::::::::::::::::::::::::::::::::::::::
data("ToothGrowth")
df <- ToothGrowth
# Kruskal-wallis rank sum test
#:::::::::::::::::::::::::::::::::::::::::
df %>% kruskal_test(len ~ dose)
#> # A tibble: 1 × 6
#> .y. n statistic df p method
#> * <chr> <int> <dbl> <int> <dbl> <chr>
#> 1 len 60 40.7 2 0.00000000148 Kruskal-Wallis
# Grouped data
df %>%
group_by(supp) %>%
kruskal_test(len ~ dose)
#> # A tibble: 2 × 7
#> supp .y. n statistic df p method
#> * <fct> <chr> <int> <dbl> <int> <dbl> <chr>
#> 1 OJ len 30 18.5 2 0.0000958 Kruskal-Wallis
#> 2 VC len 30 25.1 2 0.00000359 Kruskal-Wallis