tehtuner: Fit and Tune Models to Detect Treatment Effect Heterogeneity (original) (raw)
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 |
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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 |
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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