[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

`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")
```
