modelBasedConcordance

Calculate the model-based concordance, which is a calculation of the expected
discrimination performance of a model under the assumption the model predicts
the "TRUE" outcome as detailed in van Klaveren et al.
https://pubmed.ncbi.nlm.nih.gov/27251001/

A user friendly way to create patient level prediction models using
the Observational Medical Outcomes Partnership Common Data Model. Given a cohort
of interest and an outcome of interest, the package can use data in the Common
Data Model to build a large set of features. These features can then be used to
fit a predictive model with a number of machine learning algorithms. This is
further described in Reps (2017) <doi:10.1093/jamia/ocy032>.

Egill Fridgeirsson

PatientLevelPrediction

Develop Clinical Prediction Models Using the Common Data Model

Jenna Reps

Martijn Schuemie

Marc Suchard

Patrick Ryan

Peter Rijnbeek

Observational Health Data Science and Informatics 

modelBasedConcordance function

<dl><dt>prediction</dt>
<dd>the prediction object found in the plpResult object</dd></dl>

Arguments

Calculate the model-based concordance, which is a calculation of the expected
discrimination performance of a model under the assumption the model predicts
the "TRUE" outcome as detailed in van Klaveren et al.
https://pubmed.ncbi.nlm.nih.gov/27251001/ — modelBasedConcordance

<dl>

<dt>prediction</dt>
<dd>the prediction object found in the plpResult object</dd>

</dl>

Calculate the model-based concordance, which is a calculation of the expected
discrimination performance of a model under the assumption the model predicts
the "TRUE" outcome as detailed in van Klaveren et al.
https://pubmed.ncbi.nlm.nih.gov/27251001/

modelBasedConcordance: Calculate the model-based concordance, which is a calculation of the expected discrimination performance of a model under the assumption the model predicts the "TRUE" outcome as detailed in van Klaveren et al. https://pubmed.ncbi.nlm.nih.gov/27251001/

Description

Usage

Value

Arguments

Details

Examples