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 DOI: 10.32614/CRAN.package.tidyhte Author: Drew Dimmery [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: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=tidyhte to link to this page.
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