Evaluate median absolute deviation

Looks for the median absolute deviation values in each subgroup.

Usage

evaluate_mad(i, pheno)

Arguments

i

List of indices

pheno

Data.frame with information about the samples

Value

A vector with the mean difference between the median absolute deviation of each group and the original mad.

See also

Other functions to evaluate samples: evaluate_entropy(), evaluate_independence(), evaluate_index(), evaluate_mean(), evaluate_na(), evaluate_orig(), evaluate_sd()

Other functions to evaluate numbers: evaluate_mean(), evaluate_na(), evaluate_sd()

Examples

data(survey, package = "MASS")
index <- design(survey[, c("Sex", "Smoke", "Age")], size_subset = 50,
                iterations = 10)
#> Warning: There might be some problems with the data use check_data().
# Note that categorical columns will be omitted:
evaluate_mad(index, survey[, c("Sex", "Smoke", "Age")])
#>      Age 
#> 25.90814