vbm: Variance-Based Sensitivity Analysis for Weighting Estimators

Provides methods for variance-based sensitivity analysis and weighting estimators in observational studies based on methodology by Huang & Pimentel (2025) <doi:10.1093/biomet/asae040>. Includes bootstrap inference, bias bounds estimation, and visualization tools for sensitivity parameters.

Version: 0.1.0
Imports: parallel, magrittr, dplyr, WeightIt, estimatr, ggplot2, scales
Suggests: jointVIP, knitr, rmarkdown, pkgdown, cobalt, osqp
Published: 2026-06-30
DOI: 10.32614/CRAN.package.vbm (may not be active yet)
Author: Jiayao Gan [aut, cre], Melody Huang [aut], Samuel D. Pimentel [aut], Andy A. Shen [aut], National Science Foundation [fnd] (Grant #2142146)
Maintainer: Jiayao Gan <u3612852 at connect.hku.hk>
BugReports: https://github.com/Staniks0/vbm/issues
License: MIT + file LICENSE
URL: https://github.com/Staniks0/vbm
NeedsCompilation: no
CRAN checks: vbm results

Documentation:

Reference manual: vbm.html , vbm.pdf
Vignettes: Variance-Based Sensitivity Analysis for Weighting Estimators (source, R code)

Downloads:

Package source: vbm_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): vbm_0.1.0.tgz, r-oldrel (arm64): vbm_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): vbm_0.1.0.tgz

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