pvs {alternativeROC} | R Documentation |
Diagnostic performance: Predictive values from a ROC curve
Description
Diagnostic performance: Predictive values from a ROC curve
Usage
pvs(
roc = NULL,
prevalence,
thresholds = roc$thresholds,
sensitivities = roc$sensitivities,
specificities = roc$specificities
)
Arguments
roc |
Object of class pROC. |
prevalence |
Prevalence of the endpoint in the study population. |
thresholds |
Thresholds of the ROC curve, default is roc$thresholds. |
sensitivities |
Sensitivity values of the ROC curve, default is roc$sensitivities. |
specificities |
Specificity values of the ROC curve, default is roc$specificities. |
Details
This function computes the positive and negative predictive values from a ROC curve, given the prevalence of the positive outcome.
Value
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.
[Package alternativeROC version 1.0.0 Index]