Fligner-Killeen Test

Provides a pipe-friendly framework to perform the Fligner-Killeen test, a non-parametric (rank-based) test of the homogeneity of group variances. It is robust against departures from normality and is a useful alternative to levene_test(). Wrapper around the function fligner.test().

fligner_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 fligner.test.

Value

return a data frame with the following columns:

• .y.: the y variable used in the test.

• n: sample count.

• statistic: the Fligner-Killeen test statistic (a chi-squared statistic) used to compute the p-value.

• df: the degrees of freedom.

• p: p-value.

• method: the statistical test used to compare groups.

See also

levene_test

Examples

# Load data
#:::::::::::::::::::::::::::::::::::::::
data("ToothGrowth")
df <- ToothGrowth

# Fligner-Killeen test
#:::::::::::::::::::::::::::::::::::::::::
df %>% fligner_test(len ~ dose)
#> # A tibble: 1 × 6
#>   .y.       n statistic    df     p method         
#> * <chr> <int>     <dbl> <dbl> <dbl> <chr>          
#> 1 len      60      1.39     2 0.500 Fligner-Killeen

# Grouped data
df %>%
  group_by(supp) %>%
  fligner_test(len ~ dose)
#> # A tibble: 2 × 7
#>   supp  .y.       n statistic    df     p method         
#> * <fct> <chr> <int>     <dbl> <dbl> <dbl> <chr>          
#> 1 OJ    len      30      3.30     2 0.192 Fligner-Killeen
#> 2 VC    len      30      3.82     2 0.148 Fligner-Killeen