alternativeROC (version 1.0.1)

pvs: 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
)

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.

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.