Package: SelfControlledCohort 2.0.0

Jamie Gilbert

SelfControlledCohort: Self-Controlled Cohort Population-Level Estimation

Estimates incidence rate ratios by comparing time exposed with time unexposed among an exposed cohort using self-controlled cohort methodology as described in Ryan et al. (2013) <doi:10.1002/pds.3457>. Functions used for empirical calibration of effect estimates, confidence intervals, and p-values are included to control for residual bias.

Authors:Jamie Gilbert [cre, aut], Martijn Schuemie [aut], Patrick Ryan [aut], Observational Health Data Science and Informatics [cph]

SelfControlledCohort_2.0.0.tar.gz
SelfControlledCohort_2.0.0.zip(r-4.7)SelfControlledCohort_2.0.0.zip(r-4.6)SelfControlledCohort_2.0.0.zip(r-4.5)
SelfControlledCohort_2.0.0.tgz(r-4.6-any)SelfControlledCohort_2.0.0.tgz(r-4.5-any)
SelfControlledCohort_2.0.0.tar.gz(r-4.7-any)SelfControlledCohort_2.0.0.tar.gz(r-4.6-any)
SelfControlledCohort_2.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SelfControlledCohort/json (API)

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

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

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

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

On CRAN:

Conda:

hadesopenjdk

5.74 score 8 stars 23 scripts 222 downloads 26 exports 69 dependencies

Last updated from:173add540c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK238
source / vignettesOK280
linux-release-x86_64OK279
macos-release-arm64OK128
macos-oldrel-arm64OK104
windows-develOK173
windows-releaseOK2913
windows-oldrelOK130
wasm-releaseOK189

Exports:computeEasecomputeMdrrForRateRatiocreateExposureOutcomecreateResultsDataModelcreateRunSelfControlledCohortArgscreateSccAnalysiscreateSelfControlledCohortModuleSpecificationsexecutegetDataMigratorgetDefaultDiagnosticThresholdsgetDefaultExportManagergetDiagnosticsSummarygetModuleInfogetResultsDataModelSpecificationsgetResultsFoldersgetSccRiskWindowStatsloadExposureOutcomeListloadSccAnalysisListmigrateDataModelrunSccAnalysesrunSccDiagnosticsrunSccRiskWindowsrunSelfControlledCohortsaveExposureOutcomeListsaveSccAnalysisListuploadResults

Dependencies:Andromedabackportsbitbit64blobcheckmateclicliprcpp11crayonDatabaseConnectorDBIdbplyrdigestdplyrduckdbEmpiricalCalibrationfarverfastmapgenericsggplot2gluegridExtragtablehmsisobandjsonlitelabelinglaterlifecyclelubridatemagrittrmemuseParallelLoggerpillarpkgconfigpoolprettyunitsprogresspurrrR6rateratio.testRColorBrewerRcppreadrResultModelManagerrJavarlangrstudioapiS7scalessnowSqlRenderstringistringrtibbletidyrtidyselecttimechangetriebeardtzdburltoolsutf8vctrsviridisLitevroomwithrxml2zip

Study Diagnostics
Overview | Minimum Detectable Relative Risk (MDRR) | What it checks | Method | Interpretation | Example | Role in blinding | Pre-Exposure Gain | Why it matters | Event-Dependent Observation | Expected Absolute Systematic Error (EASE) | When it runs | Tiered Blinding | Running Diagnostics | Customizing thresholds | Selecting specific diagnostics | Inspecting failures
Rendered fromStudyDiagnostics.Rmdusingknitr::rmarkdown

Last update: 2026-06-17
Started: 2026-06-17

Using SelfControlledCohort
Setup and Data | Running a Basic Analysis | Understanding Risk Windows | Using Custom Cohorts | Diagnostics and Tiered Blinding | Empirical Calibration | Multi-Analysis Workflow | Working with the Results Database
Rendered fromUsingSelfControlledCohort.Rmdusingknitr::rmarkdown

Last update: 2026-06-17
Started: 2021-04-05

Readme and manuals

Help Manual

Help pageTopics
Compute Expected Absolute Systematic Error (EASE)computeEase
Compute Minimum Detectable Relative Risk (MDRR) for rate ratiocomputeMdrrForRateRatio
Create exposure-outcome combinations.createExposureOutcome
Create the results data model tables on a database server.createResultsDataModel
Create a parameter object for the function runSelfControlledCohortcreateRunSelfControlledCohortArgs
Create a SelfControlledCohort analysis specificationcreateSccAnalysis
Create Self-Controlled Cohort Module SpecificationscreateSelfControlledCohortModuleSpecifications
Execute Self-Controlled Cohort Analyses for Strategusexecute
Get database migrations instancegetDataMigrator
Get default diagnostic thresholdsgetDefaultDiagnosticThresholds
Get Default export managergetDefaultExportManager
Get diagnostics summarygetDiagnosticsSummary
Get module informationgetModuleInfo
Get specifications for CohortMethod results data modelgetResultsDataModelSpecifications
Get results folders for an analysis specificationgetResultsFolders
Get Self-Controlled Cohort Risk Window StatisticsgetSccRiskWindowStats
Load a list of exposureOutcome from fileloadExposureOutcomeList
Load a list of sccAnalysis from fileloadSccAnalysisList
Migrate Data modelmigrateDataModel
Run a list of analysesrunSccAnalyses
Run Self-Controlled Cohort DiagnosticsrunSccDiagnostics
Run Self-Controlled Cohort Risk WindowsrunSccRiskWindows
Run self-controlled cohortrunSelfControlledCohort
Save a list of exposureOutcome to filesaveExposureOutcomeList
Save a list of sccAnalysis to filesaveSccAnalysisList
Upload results to the database server.uploadResults