Package: DevTreatRules 1.1.0
Jeremy Roth
DevTreatRules: Develop Treatment Rules with Observational Data
Develop and evaluate treatment rules based on: (1) the standard indirect approach of split-regression, which fits regressions separately in both treatment groups and assigns an individual to the treatment option under which predicted outcome is more desirable; (2) the direct approach of outcome-weighted-learning proposed by Yingqi Zhao, Donglin Zeng, A. John Rush, and Michael Kosorok (2012) <doi:10.1080/01621459.2012.695674>; (3) the direct approach, which we refer to as direct-interactions, proposed by Shuai Chen, Lu Tian, Tianxi Cai, and Menggang Yu (2017) <doi:10.1111/biom.12676>. Please see the vignette for a walk-through of how to start with an observational dataset whose design is understood scientifically and end up with a treatment rule that is trustworthy statistically, along with an estimation of rule benefit in an independent sample.
Authors:
DevTreatRules_1.1.0.tar.gz
DevTreatRules_1.1.0.tar.gz(r-4.5-noble)DevTreatRules_1.1.0.tar.gz(r-4.4-noble)
DevTreatRules_1.1.0.tgz(r-4.4-emscripten)DevTreatRules_1.1.0.tgz(r-4.3-emscripten)
DevTreatRules.pdf |DevTreatRules.html✨
DevTreatRules/json (API)
NEWS
| # Install 'DevTreatRules' in R: |
| install.packages('DevTreatRules', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- obsStudyGeneExpressions - Simulated dataset for package 'DevTreatRule'
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:97f7d1442d. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-linux | OK | Nov 05 2024 |
Exports:BuildRuleCompareRulesOnValidationEvaluateRulePredictRuleSplitData
Dependencies:codetoolsdfoptimDynTxRegimeforeachglmnetiteratorskernlablatticeMatrixmodelObjRcppRcppEigenrgenoudshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Build a Treatment Rule | BuildRule |
| Build treatment rules on a development dataset and evaluate performance on an independent validation dataset | CompareRulesOnValidation |
| Evaluate a Treatment Rule | EvaluateRule |
| Simulated dataset for package 'DevTreatRule' | obsStudyGeneExpressions |
| Get the treatment rule implied by 'BuildRule()' | PredictRule |
| Partition a dataset into independent subsets | SplitData |