Package: prepost 0.3.0

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 et al (2025) <doi:10.1017/pan.2025.3>

Authors:Matthew Blackwell [aut, cre], Jacob Brown [aut], Sophie Hill [aut], Kosuke Imai [aut], Teppei Yamamoto [aut]

prepost_0.3.0.tar.gz
prepost_0.3.0.zip(r-4.7)prepost_0.3.0.zip(r-4.6)prepost_0.3.0.zip(r-4.5)
prepost_0.3.0.tgz(r-4.6-any)prepost_0.3.0.tgz(r-4.5-any)
prepost_0.3.0.tar.gz(r-4.7-any)prepost_0.3.0.tar.gz(r-4.6-any)
prepost_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
prepost/json (API)

# Install 'prepost' in R:
install.packages('prepost', repos = c('https://mattblackwell.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mattblackwell/prepost/issues

Pkgdown/docs site:https://mattblackwell.github.io

Datasets:

On CRAN:

Conda:

4.30 score 2 stars 4 scripts 117 downloads 8 exports 16 dependencies

Last updated from:87f64adb68. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE166
source / vignettesOK206
linux-release-x86_64NOTE146
macos-release-arm64NOTE116
macos-oldrel-arm64NOTE116
windows-develNOTE136
windows-releaseNOTE91
windows-oldrelNOTE135
wasm-releaseOK131

Exports:post_boundspost_senspre_boundspre_sensprepost_boundsprepost_gibbsprepost_gibbs_nocovarprepost_sens

Dependencies:BayesLogitclicrayongluegtoolshmslifecyclelpSolvepkgconfigprettyunitsprogressR6Rglpkrlangslamvctrs

Overview

Rendered fromprepost.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2024-10-03
Started: 2024-10-03