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Wilcoxon Test with AKP Effect Size (robust version of Cohen's d)

Source: R/utils.R
wilcox_akp_test.Rd

Perform a Wilcoxon test and calculate the Algina, Keselman, and Penfield (AKP) effect size. This is a robust version of Cohen's d.

Usage

wilcox_akp_test(data, var)

Arguments

data

A data frame containing the variables for the test.

var

A character string representing the variable to be tested against 'sex'.

Value

A tidy data frame containing the Wilcoxon test results and the AKP effect size.

Examples

df <- data.frame(
  value = c(10.1, 20.3, 30.5, 40.7, 50.9, 60.1, 70.3, 80.5, 90.7, 100.9),
  sex = c("M", "F", "M", "F", "M", "F", "M", "F", "M", "F")
)
wilcox_akp_test(df, var = "value")
#> # A tibble: 1 × 5
#>   statistic p.value method                       alternative akp_effect
#>       <dbl>   <dbl> <chr>                        <chr>            <dbl>
#> 1        15   0.690 Wilcoxon rank sum exact test two.sided        0.318