The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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.
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.