createStratifiedImputationSettings

Create the settings for using stratified imputation.

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 

createStratifiedImputationSettings function

<dl><dt>covariateId</dt>
<dd>The covariateId that needs imputed values</dd>
<dt>ageSplits</dt>
<dd>A vector of age splits in years to create age groups</dd></dl>

Arguments

Create the settings for using stratified imputation. — createStratifiedImputationSettings

<dl>

<dt>covariateId</dt>
<dd>The covariateId that needs imputed values</dd>


<dt>ageSplits</dt>
<dd>A vector of age splits in years to create age groups</dd>

</dl>

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createStratifiedImputationSettings: Create the settings for using stratified imputation.

Description

Usage

Value

Arguments

Details

Examples