The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

causalfrag: Cross-Framework Sensitivity Analysis with an OLS Crosswalk

Runs, classifies, interprets and reports sensitivity analyses for unmeasured confounding across the partial R-squared robustness value approach (Cinelli and Hazlett, 2020, <doi:10.1111/rssb.12348>), E-values (VanderWeele and Ding, 2017, <doi:10.7326/M16-2607>), and the impact threshold for a confounding variable and robustness of inference to replacement (Frank, 2000, <doi:10.1177/0049124100029002001>; Frank, Maroulis, Duong and Kelcey, 2013, <doi:10.3102/0162373713493129>). An ordinary least squares crosswalk reports the robustness values, impact threshold and replacement percentage computed from the focal t statistic and residual degrees of freedom, makes explicit that their agreement is largely fixed by that shared input, and flags the boundary band in which they disagree. Template-based plain-language reports are included, with optional integration with the 'confoundvis' package for plots.

Version: 0.2.0
Depends: R (≥ 4.1.0)
Imports: cli (≥ 3.4.0), rlang (≥ 1.0.0), jsonlite (≥ 1.8.0), glue (≥ 1.6.0)
Suggests: httr2 (≥ 1.0.0), confoundvis (≥ 0.1.0), sensemakr (≥ 0.1.4), EValue (≥ 4.1.3), konfound (≥ 0.4.0), rbounds (≥ 2.1), rmarkdown (≥ 2.14), knitr (≥ 1.39), testthat (≥ 3.0.0), withr (≥ 2.5.0)
Published: 2026-10-01
DOI: 10.32614/CRAN.package.causalfrag
Author: Subir Hait ORCID iD [aut, cre]
Maintainer: Subir Hait <haitsubi at msu.edu>
BugReports: https://github.com/subirhait/causalfrag/issues
License: MIT + file LICENSE
URL: https://github.com/subirhait/causalfrag
NeedsCompilation: no
Materials: NEWS
CRAN checks: causalfrag results

Documentation:

Reference manual: causalfrag.html , causalfrag.pdf
Vignettes: Getting started with causalfrag (source, R code)

Downloads:

Package source: causalfrag_0.2.0.tar.gz
Windows binaries: r-devel: causalfrag_0.1.1.zip, r-release: causalfrag_0.1.1.zip, r-oldrel: causalfrag_0.2.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): causalfrag_0.2.0.tgz, r-oldrel (x86_64): causalfrag_0.2.0.tgz
Old sources: causalfrag archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=causalfrag to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.