Kruskal-Wallis Test — kruskal

Provides a pipe-friendly framework to perform Kruskal-Wallis rank sum test. Wrapper around the function kruskal.test().

Usage

kruskal_test(data, formula, ...)

Arguments

data: a data.frame containing the variables in the formula.
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.

Value

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.

Examples

# 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