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.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: Rcpp, coda, stats, magrittr, purrr, abind, foreach, parallel, doParallel, ggplot2, dplyr, tidyr, metR, MASS, lme4
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Suggests: knitr, rmarkdown
Published: 2023-03-02
DOI: 10.32614/CRAN.package.aihuman
Author: Sooahn Shin ORCID iD [aut, cre], Zhichao Jiang [aut], Kosuke Imai [aut]
Maintainer: Sooahn Shin <sooahnshin at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: aihuman results


Reference manual: aihuman.pdf
Vignettes: aihuman


Package source: aihuman_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): aihuman_0.1.0.tgz, r-oldrel (arm64): aihuman_0.1.0.tgz, r-release (x86_64): aihuman_0.1.0.tgz, r-oldrel (x86_64): aihuman_0.1.0.tgz


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