computeAucFromDataFrames

A vector with the predicted hazard rate.

prediction

A vector with the status of 1 (event) or 0 (no event).

status

Only for survival models: a vector with the time to event or censor
(which ever comes first).

time

Should 95 percebt confidence intervals be computed?

confidenceInterval

Only for survival models: time point when the AUC should be evaluated

timePoint

Type of model. Currently supported are "logistic" and "survival".

modelType

Compute the area under the ROC curve

A package for creating patient level prediction models. Given a
cohort of interest and an outcome of interest, the package can use data in the
OMOP Common Data Model to build a large set of features. These features can then
be assessed to fit a predictive model using a number of machine learning algorithms.
Several performance measures are implemented for model evaluation.

computeAucFromDataFrames: Compute the area under the ROC curve

Description

Usage

Arguments

Details