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Methods for randomization inference in group-randomized trials. Specifically, it can be used to analyze the treatment effect of stratified data with multiple clusters in each stratum with treatment given on cluster level. User may also input as many covariates as they want to fit the data. Methods are described by Dylan S Small et al., (2012) <doi:10.1198/016214507000000897>.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | dplyr, randomForest, tidyverse, stats, SuperLearner, glmnet, rlang, Rdpack |
| Published: | 2023-02-22 |
| Author: | Yang Dong [aut, cph, cre], Bingkai Wang [aut, cph], Dylan Small [aut, cph] |
| Maintainer: | Yang Dong <flankado at sas.upenn.edu> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | Ricrt results |
| Reference manual: | Ricrt.pdf |
| Package source: | Ricrt_0.1.0.tar.gz |
| Windows binaries: | r-devel: Ricrt_0.1.0.zip, r-release: Ricrt_0.1.0.zip, r-oldrel: Ricrt_0.1.0.zip |
| macOS binaries: | r-release (arm64): Ricrt_0.1.0.tgz, r-oldrel (arm64): Ricrt_0.1.0.tgz, r-release (x86_64): Ricrt_0.1.0.tgz, r-oldrel (x86_64): Ricrt_0.1.0.tgz |
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