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. 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.
- Version0.1.0
- R version≥ 2.10
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release03/02/2023
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Team
Sooahn Shin
Kosuke Imai
Show author detailsRolesAuthorZhichao Jiang
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- Imports13 packages
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