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prepost: Non-Parametric Bounds and Gibbs Sampler for Assessing Priming and Post-Treatment Bias

A set of tools to implement the non-parametric bounds and Bayesian methods for assessing post-treatment bias developed in Blackwell, Brown, Hill, Imai, and Yamamoto (2025) <doi:10.1017/pan.2025.3>.

Version: 0.3.0
Depends: R (≥ 2.10)
Imports: gtools, BayesLogit, lpSolve, progress, Rglpk
Suggests: testthat (≥ 3.0.0), devtools, knitr, rmarkdown, lmtest, sandwich, dplyr, ggplot2
Published: 2025-07-07
DOI: 10.32614/CRAN.package.prepost
Author: Matthew Blackwell [aut, cre], Jacob Brown [aut], Sophie Hill [aut], Kosuke Imai [aut], Teppei Yamamoto [aut]
Maintainer: Matthew Blackwell <mblackwell at gmail.com>
License: MIT + file LICENSE
URL: https://github.com/mattblackwell/prepost, https://mattblackwell.github.io/prepost/
NeedsCompilation: no
Materials: README
CRAN checks: prepost results

Documentation:

Reference manual: prepost.pdf
Vignettes: Overview (source, R code)

Downloads:

Package source: prepost_0.3.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): prepost_0.3.0.tgz, r-oldrel (arm64): prepost_0.3.0.tgz, r-release (x86_64): prepost_0.3.0.tgz, r-oldrel (x86_64): prepost_0.3.0.tgz

Linking:

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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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