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causalfrag: Cross-Framework Causal Fragility Index

Provides a unified workflow for running, classifying, visualizing, and interpreting sensitivity analyses for unmeasured confounding across multiple causal frameworks. Introduces the Causal Fragility Index (CFI), a single 0-100 composite score that integrates evidence from the partial R-squared robustness value approach (Cinelli and Hazlett, 2020, <doi:10.1111/rssb.12348>), E-value metrics (VanderWeele and Ding, 2017, <doi:10.7326/M16-2607>), and the Impact Threshold for a Confounding Variable (Frank, 2000, <doi:10.1177/0049124100029002001>) into one interpretable measure of robustness. The package also provides template-based plain-language narrative interpretation and publication-ready reporting, with optional integration with the 'confoundvis' package for sensitivity plots.

Version: 0.1.1
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: 2026-06-15
DOI: 10.32614/CRAN.package.causalfrag (may not be active yet)
Author: Subir Hait ORCID iD [aut, cre]
Maintainer: Subir Hait <haitsubi at msu.edu>
BugReports: https://github.com/causalfragility-lab/causalfrag/issues
License: MIT + file LICENSE
URL: https://github.com/causalfragility-lab/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_0.1.1.tar.gz
Windows binaries: r-devel: not available, r-release: causalfrag_0.1.1.zip, r-oldrel: not available
macOS binaries: r-release (arm64): causalfrag_0.1.1.tgz, r-oldrel (arm64): causalfrag_0.1.1.tgz, r-release (x86_64): causalfrag_0.1.1.tgz, r-oldrel (x86_64): causalfrag_0.1.1.tgz

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.
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