Package: Characterization 3.0.1

Jenna Reps

Characterization: Implement Descriptive Studies Using the Common Data Model

An end-to-end framework that enables users to implement various descriptive studies for a given set of target and outcome cohorts for data mapped to the Observational Medical Outcomes Partnership Common Data Model.

Authors:Jenna Reps [aut, cre], Patrick Ryan [aut], Chris Knoll [aut]

Characterization_3.0.1.tar.gz
Characterization_3.0.1.zip(r-4.7)Characterization_3.0.1.zip(r-4.6)Characterization_3.0.1.zip(r-4.5)
Characterization_3.0.1.tgz(r-4.6-any)Characterization_3.0.1.tgz(r-4.5-any)
Characterization_3.0.1.tar.gz(r-4.7-any)Characterization_3.0.1.tar.gz(r-4.6-any)
Characterization_3.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
Characterization/json (API)

# Install 'Characterization' in R:
install.packages('Characterization', repos = c('https://ohdsi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ohdsi/characterization/issues

Pkgdown/docs site:https://ohdsi.github.io

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT

On CRAN:

Conda:

openjdk

6.18 score 3 stars 28 scripts 304 downloads 21 exports 61 dependencies

Last updated from:ca4f13f410. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK266
source / vignettesOK238
linux-release-x86_64OK266
macos-release-arm64OK198
macos-oldrel-arm64OK230
windows-develOK236
windows-releaseOK256
windows-oldrelOK243
wasm-releaseOK155

Exports:cleanIncrementalcleanNonIncrementalcomputeDechallengeRechallengeAnalysescomputeRechallengeFailCaseSeriesAnalysescomputeTimeToEventAnalysescreateCaseSeriesSettingscreateCharacterizationSettingscreateCharacterizationTablescreateDechallengeRechallengeSettingscreateDuringCovariateSettingscreateRiskFactorSettingscreateSqliteDatabasecreateTargetBaselineSettingscreateTimeToEventSettingsexampleOmopConnectionDetailsgetDbDuringCovariateDatainsertResultsToDatabaseloadCharacterizationSettingsrunCharacterizationAnalysessaveCharacterizationSettingsviewCharacterization

Dependencies:Andromedabackportsbitbit64blobcachemcheckmateclicliprcpp11crayonDatabaseConnectorDBIdbplyrdigestdplyrduckdbfastmapFeatureExtractiongenericsgluehmsjsonlitelaterlifecyclelubridatemagrittrmemoisememuseParallelLoggerpillarpkgconfigpoolprettyunitsprogresspurrrR6RcppreadrResultModelManagerrJavarlangRSQLiterstudioapisnowSqlRenderstringistringrtibbletidyrtidyselecttimechangetriebeardtzdburltoolsutf8vctrsvroomwithrxml2zip

Characterization Package Specification

Jenna Reps

Rendered fromSpecification.Rmdusingknitr::knitron May 15 2026.

Last update: 2026-03-18
Started: 2024-12-06

Using Characterization Package

Jenna Reps

Rendered fromUsingPackage.Rmdusingknitr::knitron May 15 2026.

Last update: 2026-05-15
Started: 2024-08-09

Readme and manuals

Help Manual

Help pageTopics
Removes csv files from folders that have not been marked as completed and removes the record of the execution filecleanIncremental
Removes csv files from the execution folder as there should be no csv files when running in non-incremental modelcleanNonIncremental
Compute dechallenge rechallenge studycomputeDechallengeRechallengeAnalyses
Compute fine the subjects that fail the dechallenge rechallenge studycomputeRechallengeFailCaseSeriesAnalyses
Compute time to event studycomputeTimeToEventAnalyses
Create aggregate covariate study settingscreateCaseSeriesSettings
Create the settings for a large scale characterization studycreateCharacterizationSettings
Create the results tables to store characterization results into a databasecreateCharacterizationTables
Create dechallenge rechallenge study settingscreateDechallengeRechallengeSettings
Create during covariate settingscreateDuringCovariateSettings
Create risk factor study settingscreateRiskFactorSettings
Create an sqlite database connectioncreateSqliteDatabase
Create target baseline aggregate covariate study settingscreateTargetBaselineSettings
Create time to event study settingscreateTimeToEventSettings
create a connection detail for an example GI Bleed dataset from EunomiaexampleOmopConnectionDetails
Extracts covariates that occur during a cohortgetDbDuringCovariateData
Upload the results into a result databaseinsertResultsToDatabase
Load the characterization settings previously saved as a json fileloadCharacterizationSettings
execute a large-scale characterization studyrunCharacterizationAnalyses
Save the characterization settings as a jsonsaveCharacterizationSettings
viewCharacterization - Interactively view the characterization resultsviewCharacterization