tidyhte: Tidy Estimation of Heterogeneous Treatment Effects

Estimates heterogeneous treatment effects using tidy semantics on experimental or observational data. Methods are based on the doubly-robust learner of Kennedy (n.d.) <doi:10.48550/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.

Version: 1.0.2
Imports: checkmate, dplyr, lifecycle, magrittr, progress, purrr, R6, rlang, SuperLearner, tibble
Suggests: covr, devtools, estimatr, ggplot2, glmnet, knitr, mockr, nprobust, palmerpenguins, quadprog, quickblock, rmarkdown, testthat (≥ 3.0.0), vimp, WeightedROC
Published: 2023-08-14
Author: Drew Dimmery ORCID iD [aut, cre, cph]
Maintainer: Drew Dimmery <drew.dimmery at univie.ac.at>
BugReports: https://github.com/ddimmery/tidyhte/issues
License: MIT + file LICENSE
URL: https://github.com/ddimmery/tidyhte https://ddimmery.github.io/tidyhte/index.html
NeedsCompilation: no
Materials: README NEWS
CRAN checks: tidyhte results

Documentation:

Reference manual: tidyhte.pdf
Vignettes: HTE Analysis in an Experiment
Methodological Details
HTE Analysis on Observational Data

Downloads:

Package source: tidyhte_1.0.2.tar.gz
Windows binaries: r-devel: tidyhte_1.0.2.zip, r-release: tidyhte_1.0.2.zip, r-oldrel: tidyhte_1.0.2.zip
macOS binaries: r-release (arm64): tidyhte_1.0.2.tgz, r-oldrel (arm64): tidyhte_1.0.2.tgz, r-release (x86_64): tidyhte_1.0.2.tgz

Linking:

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