computeAucFromDataFrames: Compute the area under the ROC curve

In hxia/plp-git-demo: Package for patient level prediction using data in the OMOP Common Data Model

Description

Compute the area under the ROC curve

Usage

computeAucFromDataFrames(
  prediction,
  status,
  time = NULL,
  confidenceInterval = FALSE,
  timePoint,
  modelType = "logistic"
)

Arguments

prediction	A vector with the predicted hazard rate.
status	A vector with the status of 1 (event) or 0 (no event).
time	Only for survival models: a vector with the time to event or censor (which ever comes first).
confidenceInterval	Should 95 percebt confidence intervals be computed?
timePoint	Only for survival models: time point when the AUC should be evaluated
modelType	Type of model. Currently supported are "logistic" and "survival".

Details

Computes the area under the ROC curve for the predicted probabilities, given the true observed outcomes.

hxia/plp-git-demo documentation built on March 19, 2021, 1:54 a.m.