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
Author: Sooahn Shin ORCID iD [aut, cre], Zhichao Jiang [aut], Kosuke Imai [aut]
Maintainer: Sooahn Shin <sooahnshin at g.harvard.edu>
BugReports: https://github.com/sooahnshin/aihuman/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/sooahnshin/aihuman
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: aihuman results

Documentation:

Reference manual: aihuman.pdf
Vignettes: aihuman

Downloads:

Package source: aihuman_0.1.0.tar.gz
Windows binaries: r-devel: aihuman_0.1.0.zip, r-release: aihuman_0.1.0.zip, r-oldrel: aihuman_0.1.0.zip
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

Linking:

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