Implements methods to fit Virtual Twins models (Foster et al. (2011) <doi:10.1002/sim.4322>) for identifying subgroups with differential effects in the context of clinical trials while controlling the probability of falsely detecting a differential effect when the conditional average treatment effect is uniform across the study population using parameter selection methods proposed in Wolf et al. (2022) <doi:10.1177/17407745221095855>.
Version: 0.3.0 Depends: R (≥ 3.5.0) Imports: party, glmnet, Rdpack, rpart, stringr, SuperLearner, randomForestSRC, earth, foreach Suggests: knitr, rmarkdown, spelling, testthat (≥ 3.0.0) Published: 2023-04-01 DOI: 10.32614/CRAN.package.tehtuner Author: Jack Wolf [aut, cre] Maintainer: Jack Wolf <jackwolf910 at gmail.com> BugReports: https://github.com/jackmwolf/tehtuner/issues License: GPL (≥ 3) URL: https://github.com/jackmwolf/tehtuner NeedsCompilation: no Language: en-US Citation: tehtuner citation info Materials: README NEWS CRAN checks: tehtuner results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=tehtuner to link to this page.
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