getPlpData

This function executes a large set of SQL statements against the database in OMOP CDM format to
extract the data needed to perform the analysis.

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 

getPlpData function

<dl><dt>databaseDetails</dt>
<dd>The cdm database details created using <code>createDatabaseDetails()</code></dd>
<dt>covariateSettings</dt>
<dd>An object of type <code>covariateSettings</code> or a list of such objects as created using the
<code>createCovariateSettings</code> function in the
<code>FeatureExtraction</code> package.</dd>
<dt>restrictPlpDataSettings</dt>
<dd>Extra settings to apply to the target population while extracting data.
Created using <code>createRestrictPlpDataSettings()</code>. This is optional.</dd></dl>

Arguments

Extract the patient level prediction data from the server — getPlpData

<dl>

<dt>databaseDetails</dt>
<dd>The cdm database details created using <code>createDatabaseDetails()</code></dd>


<dt>covariateSettings</dt>
<dd>An object of type <code>covariateSettings</code> or a list of such objects as created using the
<code>createCovariateSettings</code> function in the
<code>FeatureExtraction</code> package.</dd>


<dt>restrictPlpDataSettings</dt>
<dd>Extra settings to apply to the target population while extracting data.
Created using <code>createRestrictPlpDataSettings()</code>. This is optional.</dd>

</dl>

getPlpData: Extract the patient level prediction data from the server

Description

Usage

Value

Arguments

Details