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

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

## Documentation for package ‘prepost’ version 0.3.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

delponte | Replication dataset from Del Ponte (2020)
land_experiment | Replication dataset from Horowitz and Klaus (2020)
post_bounds | Run post-treatment bounds.
post_sens | Run sensitivity analysis on post-measurement design
prepost_bounds | Run Prepost bounds
prepost_gibbs | Run Gibbs sampler for the random moderator placement design
prepost_gibbs_nocovar | Run Gibbs sampler without covariates
prepost_sens | Run sensitivity analysis for the randomized moderator placement design
pre_bounds | Run pre-treatment bounds.
pre_sens | Run sensitivity analysis on pre-test design