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 (may not be active yet) |
| 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 |
Documentation:
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