Experimental Evaluation of Algorithm-Assisted Human Decision-Making R package aihuman version 1.0.1 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. Software 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 Sooahn Shin <sooahnshin@g.harvard.edu> Comprehensive R Archive Network (CRAN) Sooahn Shin [aut, cre] (ORCID: <https://orcid.org/0000-0001-6213-2197>), Zhichao Jiang [aut], Kosuke Imai [aut] GPL (>= 2) 2025-05-07 application/tgz https://CRAN.R-project.org/package=aihuman doi:10.32614/CRAN.package.aihuman