aihuman
Experimental Evaluation of Algorithm-Assisted Human Decision-Making
Provides statistical methods for analyzing experimental evaluation of the causal impacts of algorithmic recommendations on human decisions developed by Imai, Jiang, Greiner, Halen, and Shin (2023) doi:10.1093/jrsssa/qnad010 and Ben-Michael, Greiner, Huang, Imai, Jiang, and Shin (2024) doi:10.48550/arXiv.2403.12108. The data used for this paper, and made available here, are interim, based on only half of the observations in the study and (for those observations) only half of the study follow-up period. We use them only to illustrate methods, not to draw substantive conclusions.
- Version1.0.1
- R versionR (≥ 4.1.0)
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- aihuman citation info
- Last release05/07/2025
Documentation
Team
Sooahn Shin
MaintainerShow author detailsZhichao Jiang
Show author detailsRolesAuthorKosuke Imai
Show author detailsRolesAuthor
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- Imports17 packages
- Suggests2 packages
- Linking To3 packages