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whatifbandit  

Analyzing Randomized Experiments as Multi-Arm Bandits
View on CRAN: Click here


Download and install whatifbandit package within the R console
Install from CRAN:
install.packages("whatifbandit")

Install from Github:
library("remotes")
install_github("cran/whatifbandit")

Install by package version:
library("remotes")
install_version("whatifbandit", "0.3.0")



Attach the package and use:
library("whatifbandit")
Maintained by
Noah Ochital
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-03
Latest Update: 2025-11-03
Description:
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>.
How to cite:
Noah Ochital (2025). whatifbandit: Analyzing Randomized Experiments as Multi-Arm Bandits. R package version 0.3.0, https://cran.r-project.org/web/packages/whatifbandit. Accessed 22 Sep. 2026.
Previous versions and publish date:
(2026-08-22 10:54), 0.3.0 (2025-11-03 11:20), 1.0.2 (2026-07-23 12:50)
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Complete documentation for whatifbandit
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