abs_d_sens_spec: Calculate the absolute difference of sensitivity and...

In cutpointr: Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks

Calculate the absolute difference of sensitivity and specificity

Description

Calculate the absolute difference of sensitivity and specificity from true positives, false positives, true negatives and false negatives. The inputs must be vectors of equal length.

sensitivity = tp / (tp + fn)
specificity = tn / (tn + fp)
abs_d_sens_spec = |sensitivity - specificity|

Usage

abs_d_sens_spec(tp, fp, tn, fn, ...)

Arguments

tp	(numeric) number of true positives.
fp	(numeric) number of false positives.
tn	(numeric) number of true negatives.
fn	(numeric) number of false negatives.
...	for capturing additional arguments passed by method.

See Also

Other metric functions: F1_score(), Jaccard(), abs_d_ppv_npv(), accuracy(), cohens_kappa(), cutpoint(), false_omission_rate(), metric_constrain(), misclassification_cost(), npv(), odds_ratio(), p_chisquared(), plr(), ppv(), precision(), prod_ppv_npv(), prod_sens_spec(), recall(), risk_ratio(), roc01(), sensitivity(), specificity(), sum_ppv_npv(), sum_sens_spec(), total_utility(), tpr(), tp(), youden()

Examples

abs_d_sens_spec(10, 5, 20, 10)
abs_d_sens_spec(c(10, 8), c(5, 7), c(20, 12), c(10, 18))

cutpointr documentation built on April 14, 2022, 1:06 a.m.