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.
| Version: | 1.0.0 |
| Imports: | stats |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2026-07-02 |
| DOI: | 10.32614/CRAN.package.mixedsubjects |
| Author: | Austin van Loon [aut], Klint Kanopka [aut, cre], Yuan Huang [ctb] |
| Maintainer: | Klint Kanopka <klint.kanopka at nyu.edu> |
| BugReports: | https://github.com/klintkanopka/mixedsubjects/issues |
| License: | MIT + file LICENSE |
| URL: | https://klintkanopka.com/mixedsubjects/ |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | mixedsubjects results |
| Package source: | mixedsubjects_1.0.0.tar.gz |
| Windows binaries: | r-devel: mixedsubjects_1.0.0.zip, r-release: mixedsubjects_1.0.0.zip, r-oldrel: mixedsubjects_1.0.0.zip |
| macOS binaries: | r-release (arm64): mixedsubjects_1.0.0.tgz, r-oldrel (arm64): mixedsubjects_1.0.0.tgz, r-release (x86_64): mixedsubjects_1.0.0.tgz, r-oldrel (x86_64): mixedsubjects_1.0.0.tgz |
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