cutpointr (version 1.1.2)

abs_d_ppv_npv: Calculate the absolute difference of positive and negative predictive value

Description

Calculate the absolute difference of positive predictive value (PPV) and negative predictive value (NPV) from true positives, false positives, true negatives and false negatives. The inputs must be vectors of equal length. ppv = tp / (tp + fp) npv = tn / (tn + fn) abs\_d\_ppv\_npv = |ppv - npv|

Usage

abs_d_ppv_npv(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_sens_spec(), 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

# NOT RUN {
abs_d_ppv_npv(10, 5, 20, 10)
abs_d_ppv_npv(c(10, 8), c(5, 7), c(20, 12), c(10, 18))
# }