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prepost: Non-Parametric Bounds and Gibbs Sampler for Assessing Primingand 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 + fileLICENSE
URL:https://github.com/mattblackwell/prepost,https://mattblackwell.github.io/prepost/
NeedsCompilation:no
Materials:README
CRAN checks:prepost results

Documentation:

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

Downloads:

Package source: prepost_0.3.0.tar.gz
Windows binaries: r-devel:prepost_0.3.0.zip, r-release:prepost_0.3.0.zip, r-oldrel:prepost_0.3.0.zip
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:

Please use the canonical formhttps://CRAN.R-project.org/package=prepostto link to this page.


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