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.
Version: 1.0.1 Depends: R (≥ 4.1.0) Imports: Rcpp, coda, stats, magrittr, purrr, abind, foreach, parallel, doParallel, ggplot2, dplyr, tidyr, metR, MASS, GLMMadaptive, gbm, tidyselect, stringr, forcats LinkingTo: Rcpp, RcppArmadillo, RcppEigen Suggests: knitr, rmarkdown Published: 2025-05-07 DOI: 10.32614/CRAN.package.aihuman Author: Sooahn Shin [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 Citation: aihuman citation info Materials: README NEWS CRAN checks: aihuman results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=aihuman to link to this page.
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