tehtuner: Fit and Tune Models to Detect Treatment Effect Heterogeneity
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 |
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