| abs_d_ppv_npv {cutpointr} | R Documentation |
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
abs_d_ppv_npv(10, 5, 20, 10)
abs_d_ppv_npv(c(10, 8), c(5, 7), c(20, 12), c(10, 18))