R Observatory: Metrics for SelfControlledCohort version 2.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

SelfControlledCohort

2.1.0Package record

Self-Controlled Cohort Population-Level Estimation

0packages depend

1.4Kdownloads / year

88.9%test coverage

13/13flavors OK

Overview

About

Maintained by Jamie GilbertCRAN page ↗GitHub ↗Website ↗Issues ↗

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.

Changes in 2.1.0

Changes:

Performance: MDRR, pre-exposure gain, event-dependent observation, and EASE diagnostics now use batched SQL reads and ParallelLogger-based parallelism, and no longer materialize full result sets in memory.
Study diagnostics are now configurable via Strategus through createRunSelfControlledCohortArgs() (runDiagnostics, diagnostics, diagnosticThresholds).
Added a CohortGenerator dependency; execute() now validates that all requested exposure/outcome cohorts were generated (present in the cohort checksum table).

Bug Fixes:

Fixed a bug where exposure-based negative controls (controlType = "exposure") were treated as outcomes, contaminating outcome_cohort_id in results.
Fixed scc_outcome_exposure to reflect the full input exposure-outcome list (rather than only pairs with results) and to correctly accumulate scc_result across all calibration groups/batches.
scc_result, scc_stat, scc_diagnostics_summary, and scc_outcome_exposure are now always exported (as empty files when an analysis yields no effect estimates), so the export folder and manifest stay consistent.
scc_outcome_exposure no longer emits exposure-outcome pairs with missing cohort IDs, which previously violated the NOT NULL primary key constraints on results upload.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("SelfControlledCohort", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("OHDSI/SelfControlledCohort")

Development version from OHDSI/SelfControlledCohort. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-selfcontrolledcohort

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-SelfControlledCohort

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-SelfControlledCohort

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 7.7 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-10-18
ERROR10 OK, 3 ERROR2026-10-09
OK13 OK2026-09-29
ERROR12 OK, 1 ERROR2026-09-04
OK13 OK2026-08-05

Show 4 earlier changesHide 4 earlier changes

NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-29
ERROR12 OK, 1 ERROR2026-06-27
OK7 OK2026-06-18

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 2.1.0

READMEYes · 199 wordsVignettesYes · 2 · dynamicNEWSYes · 33% structured · mentions 2.1.0Citation fileNoWebsiteYes · pkgdown

Help pages: 28 (2 internal)includes a package overview page
Examples that run: 0%26 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 100%
Documented parameters: 98%
Return-value docs: 100%
Help pages citing references: 11%

Vignettes (2)

How these are measured

Downloads

1.4K

CRAN downloads in the past year

Rank #10,679 · ~4/day · ~117/mo

Releases R versions

Daily download trend is not available in this view yet.

37330 days

96790 days

1.4K1 year

Compare downloads with other packages →

Also on22 r2u1 autocran

How downloads are counted

Repository

ohdsi/selfcontrolledcohort ↗Organization: OHDSI

8Stars

4Forks

2Open issues

0Open PRs

4Releases

159Commits

9Commit identities

hades

License file reads as Apache-2.0 · 159 commits · Last activity 2026-10-07

Responsiveness

How these are sampled

PRs merged (all time): 92%
Median days to close, 50 most recently updated closed issues: 18
Median days to close, 50 most recently updated closed PRs: 5

Stars over time

2024-09-17 · 82026-07-07 · 8

How these are measured

PracticesBeta

10 development-tooling and community-health practices detected across 7 families in the upstream repository

Checks run against github.com/ohdsi/selfcontrolledcohort on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows

Governance and community (1)

PR template

Docs source (2)

pkgdown

GitHub Pages site last deployed 2026-10-07

Coverage (1)

Coverage reporting

Show all practicesHide 3 practices

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

Git structural (1)

.gitattributes

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

30 external dependencies (excludes base and recommended)

Installing SelfControlledCohort adds 70 packages (37 with compiled code, 49 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, duckdb 4.6 MB.

Depends (2)

R >= 4.1.0DatabaseConnector

Imports (13)

SqlRender ParallelLogger rateratio.test checkmate dplyr EmpiricalCalibration ResultModelManager Andromeda readr rlang clistatsCohortGenerator

LinkingTo (0)

none

Suggests (17)

withr testthat knitr rmarkdown Eunomia duckdb DiagrammeR tidyr R.utils jsonlite DT ggplot2 shiny shinycssloaders plotly reactable shinyWidgets

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (4)

Jamie Gilbert

Maintainer since 2.0.0 (2026), Author

Patrick Ryan

Author

Martijn Schuemie

Author

Observational Health Data Science and Informatics

Copyright holder

Releases (2)

Pick two releases to compare their code metrics.

2.1.0Latest
record
2026-10-07 · current release · diff ↗
2.0.0
record
2026-06-17
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-06-17
Total releases: 2 / 1 yrs
License: Apache License 2.0 OSI
Minimum R: ≥ 4.1.0
Download size: 231 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SelfControlledCohort")

Format

Gilbert, J., Observational Health Data Science and Informatics, Ryan, P., & Schuemie, M. (2026). SelfControlledCohort: Self-Controlled Cohort Population-Level Estimation (Version 2.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.SelfControlledCohort

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SelfControlledCohort version 2.1.0 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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