Omitted Variable Tool
Overview
This tool was designed to assess the sensitivity of research findings to omitted variables when estimating causal effects using propensity score (PS) weighting. This tool produces graphics and summary results that will enable a researcher to quantify the impact an omitted variable would have on their results. Burgette et al. (2021) describe the methodology behind the primary function in this package, ov_sim. The method is demonstrated in Griffin et al. (2020) doi:10.1016/j.jsat.2020.108075.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 13
- Examples that run
- 100%13 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 8%
Downloads
Dependencies
Code & Tests
Datasets
People & History
Previously maintained by Joseph Pane (1.0.0 to 1.0.2).
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- unarchivedReturned to CRAN2021-11-02
- 1.0.3Latest
- archivedRemoved from CRAN2021-10-06email to the maintainer was undeliverable
- 1.0.22021-08-18 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 1.0.12021-04-19 · diff ↗
- 1.0.02021-03-18
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2021-03-18
- Total releases
- 4 / 5 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 154 KB / 1 file
- Download size
- 2.6 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("OVtool")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
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