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mixedsubjects is a package for conducting social science experiments using the Mixed-Subjects Design and estimating causal effects. It 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.

Installation

Interested users can install using:

# install.packages("remotes")
remotes::install_github("klintkanopka/mixedsubjects")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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