aihuman-package {aihuman} | R Documentation |
Experimental Evaluation of Algorithm-Assisted Human Decision-Making
Description
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.
Package Content
Index of help topics:
APCEsummary Summary of APCE APCEsummaryipw Summary of APCE for frequentist analysis AiEvalmcmc Gibbs sampler for the main analysis BootstrapAPCEipw Bootstrap for estimating variance of APCE BootstrapAPCEipwRE Bootstrap for estimating variance of APCE with random effects BootstrapAPCEipwREparallel Bootstrap for estimating variance of APCE with random effects CalAPCE Calculate APCE CalAPCEipw Compute APCE using frequentist analysis CalAPCEipwRE Compute APCE using frequentist analysis with random effects CalAPCEparallel Calculate APCE using parallel computing CalDIM Calculate diff-in-means estimates CalDIMsubgroup Calculate diff-in-means estimates CalDelta Calculate the delta given the principal stratum CalFairness Calculate the principal fairness CalOptimalDecision Calculate optimal decision & utility CalPS Calculate the proportion of principal strata (R) FTAdata Interim Dane data with failure to appear (FTA) as an outcome HearingDate Interim court event hearing date NCAdata Interim Dane data with new criminal activity (NCA) as an outcome NVCAdata Interim Dane data with new violent criminal activity (NVCA) as an outcome PSAdata Interim Dane PSA data PlotAPCE Plot APCE PlotDIMdecisions Plot diff-in-means estimates PlotDIMoutcomes Plot diff-in-means estimates PlotFairness Plot the principal fairness PlotOptimalDecision Plot optimal decision PlotPS Plot the proportion of principal strata (R) PlotSpilloverCRT Plot conditional randomization test PlotSpilloverCRTpower Plot power analysis of conditional randomization test PlotStackedBar Stacked barplot for the distribution of the decision given psa PlotStackedBarDMF Stacked barplot for the distribution of the decision given DMF recommendation PlotUtilityDiff Plot utility difference PlotUtilityDiffCI Plot utility difference with 95 interval SpilloverCRT Conduct conditional randomization test SpilloverCRTpower Conduct power analysis of conditional randomization test TestMonotonicity Test monotonicity TestMonotonicityRE Test monotonicity with random effects aihuman-package Experimental Evaluation of Algorithm-Assisted Human Decision-Making compute_bounds_aipw Compute Risk (AI v. Human) compute_nuisance_functions Fit outcome/decision and propensity score models compute_nuisance_functions_ai Fit outcome/decision and propensity score models conditioning on the AI recommendation compute_stats Compute Risk (Human+AI v. Human) compute_stats_agreement Agreement of Human and AI Decision Makers compute_stats_aipw Compute Risk (Human+AI v. Human) compute_stats_subgroup Compute Risk (Human+AI v. Human) for a Subgroup Defined by AI Recommendation crossfit Crossfitting for nuisance functions g_legend Pulling ggplot legend hearingdate_synth Synthetic court event hearing date plot_agreement Visualize Agreement plot_diff_ai_aipw Visualize Difference in Risk (AI v. Human) plot_diff_human Visualize Difference in Risk (Human+AI v. Human) plot_diff_human_aipw Visualize Difference in Risk (Human+AI v. Human) plot_diff_subgroup Visualize Difference in Risk (Human+AI v. Human) for a Subgroup Defined by AI Recommendation plot_preference Visualize Preference psa_synth Synthetic PSA data synth Synthetic data table_agreement Table of Agreement
Maintainer
Sooahn Shin <sooahnshin@g.harvard.edu>
Author(s)
Sooahn Shin [aut, cre] (<https://orcid.org/0000-0001-6213-2197>), Zhichao Jiang [aut], Kosuke Imai [aut]