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