whatifbandit: Analyzing Randomized Experiments as Multi-Arm Bandits
Simulates the results of completed randomized controlled trials, as if they had been conducted as adaptive Multi-Arm Bandit (MAB) trials instead. Augmented inverse probability weighted estimation (AIPW), outlined by Hadad et al. (2021) <doi:10.1073/pnas.2014602118>, is used to robustly estimate the probability of success for each treatment arm under the adaptive design. Provides customization options to simulate perfect/imperfect information, stationary/non-stationary bandits, blocked treatment assignments, along with control augmentation, and other hybrid strategies for assigning treatment arms. The methods used in simulation were inspired by Offer-Westort et al. (2021) <doi:10.1111/ajps.12597>.
| Version: | 0.3.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | bandit,data.table,dplyr,furrr,ggplot2,lubridate,purrr,randomizr,rlang,tibble,tidyr |
| Suggests: | future,knitr,rmarkdown,testthat (≥ 3.0.0) |
| Published: | 2025-11-03 |
| DOI: | 10.32614/CRAN.package.whatifbandit |
| Author: | Noah Ochital [aut, cre, cph], Ryan T. Moore [ctb, cph] |
| Maintainer: | Noah Ochital <noahochital at icloud.com> |
| BugReports: | https://github.com/Noch05/whatifbandit/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/Noch05/whatifbandit |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | whatifbandit results |
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