adjustr: Stan Model Adjustments and Sensitivity Analyses using Importance Sampling

Assess the sensitivity of a Bayesian model (fitted using 'Stan' via 'rstan', 'brms', or 'cmdstanr') to the specification of its likelihood and priors. Users provide a series of alternate sampling specifications, and the package uses Pareto-smoothed importance sampling (PSIS) to estimate posterior quantities of interest under each specification, without needing to refit the model. Methods are based on Vehtari, Simpson, Gelman, Yao, and Gabry (2024) <doi:10.48550/arXiv.1507.02646>.

Version: 0.2.0
Depends: R (≥ 3.6.0), dplyr (≥ 1.0.0)
Imports: rlang, tidyselect, rstan, loo
Suggests: ggplot2, extraDistr, tidyr, testthat, covr, knitr, rmarkdown
Published: 2026-05-29
DOI: 10.32614/CRAN.package.adjustr (may not be active yet)
Author: Cory McCartan [aut, cre, cph]
Maintainer: Cory McCartan <mccartan at psu.edu>
BugReports: https://github.com/CoryMcCartan/adjustr/issues
License: MIT + file LICENSE
URL: https://corymccartan.com/adjustr/
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: adjustr results

Documentation:

Reference manual: adjustr.html , adjustr.pdf
Vignettes: Sensitivity Analysis of a Simple Hierarchical Model (source, R code)

Downloads:

Package source: adjustr_0.2.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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