Diagnostic performance: Predictive values from a ROC curve
pvs(
roc = NULL,
prevalence,
thresholds = roc$thresholds,
sensitivities = roc$sensitivities,
specificities = roc$specificities
)A data frame with the following columns:
threshold: Thresholds of the ROC curve.
sensitivity: Sensitivity values of the ROC curve.
specificity: Specificity values of the ROC curve.
prevalence: Prevalence of the positive outcome.
ppv: Positive predictive value.
npv: Negative predictive value.
Object of class pROC.
Prevalence of the endpoint in the study population.
Thresholds of the ROC curve, default is roc$thresholds.
Sensitivity values of the ROC curve, default is roc$sensitivities.
Specificity values of the ROC curve, default is roc$specificities.
This function computes the positive and negative predictive values from a ROC curve, given the prevalence of the positive outcome.