confoundvis: Visualization Tools for Sensitivity Analysis of Unmeasured Confounding

Visualization and reporting tools for sensitivity analysis to unmeasured confounding in observational studies. A common 'confoundsens' object stores a sensitivity path (the treatment effect as a function of hypothetical confounder strength) regardless of the framework that produced it, so the same robustness curves, contour plots, covariate benchmark ("sensitivity Love") plots, and plain-language reports can be drawn for impact threshold analysis (Frank, 2000, <doi:10.1177/0049124100029002001>), partial R-squared omitted-variable bias analysis (Cinelli and Hazlett, 2020, <doi:10.1111/rssb.12348>), and E-values (VanderWeele and Ding, 2017, <doi:10.7326/M16-2607>). Paths can be computed directly from fitted linear models or converted from results produced by the 'sensemakr', 'konfound', and 'EValue' packages.

Version:	0.2.0
Depends:	R (≥ 4.1.0)
Imports:	ggplot2 (≥ 3.4.0), rlang, graphics, grid, stats
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown, gridExtra, sensemakr, konfound, EValue
Published:	2026-09-30
DOI:	10.32614/CRAN.package.confoundvis
Author:	Subir Hait [aut, cre]
Maintainer:	Subir Hait <haitsubi at msu.edu>
BugReports:	https://github.com/subirhait/confoundvis/issues
License:	GPL-3
URL:	https://github.com/subirhait/confoundvis
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	confoundvis results

Documentation:

Reference manual:	confoundvis.html , confoundvis.pdf
Vignettes:	Introduction to confoundvis (source, R code) From a fitted model to a sensitivity report (source, R code)

Downloads:

Package source:	confoundvis_0.2.0.tar.gz
Windows binaries:	r-devel: confoundvis_0.2.0.zip, r-release: confoundvis_0.1.0.zip, r-oldrel: confoundvis_0.2.0.zip
macOS binaries:	r-release (arm64): confoundvis_0.2.0.tgz, r-oldrel (arm64): confoundvis_0.2.0.tgz, r-release (x86_64): confoundvis_0.2.0.tgz, r-oldrel (x86_64): confoundvis_0.2.0.tgz
Old sources:	confoundvis archive

Reverse dependencies:

Reverse suggests:

causalfrag

Linking:

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