tidyhte-package {tidyhte} | R Documentation |
tidyhte: Tidy Estimation of Heterogeneous Treatment Effects
Description
Estimates heterogeneous treatment effects using tidy semantics on experimental or observational data. Methods are based on the doubly-robust learner of Kennedy (n.d.) arXiv:2004.14497. You provide a simple recipe for what machine learning algorithms to use in estimating the nuisance functions and 'tidyhte' will take care of cross-validation, estimation, model selection, diagnostics and construction of relevant quantities of interest about the variability of treatment effects.
Details
The best place to get started with tidyhte
is vignette("experimental_analysis")
which
walks through a full analysis of HTE on simulated data, or vignette("methodological_details")
which gets into more of the details underlying the method.
Author(s)
Maintainer: Drew Dimmery drew.dimmery@univie.ac.at (ORCID) [copyright holder]
References
Kennedy, E. H. (2020). Towards optimal doubly robust estimation of heterogeneous causal effects. arXiv preprint arXiv:2004.14497.
See Also
The core public-facing functions are make_splits
, produce_plugin_estimates
,
construct_pseudo_outcomes
and estimate_QoI
. Configuration is accomplished through HTE_cfg
in addition to a variety of related classes (see basic_config
).