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mixedsubjects  

Causal Inference in Experiments with Mixed-Subjects Designs
View on CRAN: Click here


Download and install mixedsubjects package within the R console
Install from CRAN:
install.packages("mixedsubjects")

Install from Github:
library("remotes")
install_github("cran/mixedsubjects")

Install by package version:
library("remotes")
install_version("mixedsubjects", "1.0.0")



Attach the package and use:
library("mixedsubjects")
Maintained by
Klint Kanopka
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All associated links for this package
First Published: 2026-07-02
Latest Update: 2026-07-02
Description:
Implements seven estimators for average treatment effect (ATE) estimation in mixed-subjects designs (MSDs), where human subjects data is augmented with predictions from large language models (LLMs). Includes Difference-in-Means, GREG, PPI++, Doubly-Tuned, Difference-in-Predictions (DiP), DiP++, and D-T DiP estimators. Provides point estimates, variance estimation via delta-method or bootstrap, and optimal design selection for budget allocation between human observations and LLM predictions.
How to cite:
Klint Kanopka (2026). mixedsubjects: Causal Inference in Experiments with Mixed-Subjects Designs. R package version 1.0.0, https://cran.r-project.org/web/packages/mixedsubjects. Accessed 27 Oct. 2026.
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