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DevTreatRules
View on CRAN: Click
here
Download and install DevTreatRules package within the R console
Install from CRAN:
install.packages("DevTreatRules")
Install from Github:
library("remotes")
install_github("cran/DevTreatRules")
Install by package version:
library("remotes")
install_version("DevTreatRules", "1.1.0")
Attach the package and use:
library("DevTreatRules")
Maintained by
Jeremy Roth
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-16
Latest Update: 2020-03-20
Description:
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) ; (3) the direct approach, which we refer to as direct-interactions, proposed by Shuai Chen, Lu Tian, Tianxi Cai, and Menggang Yu (2017) . 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.
How to cite:
Jeremy Roth (2019). DevTreatRules: Develop Treatment Rules with Observational Data. R package version 1.1.0, https://cran.r-project.org/web/packages/DevTreatRules
Previous versions and publish date:
1.0.0 (2019-05-16 13:20)
Other packages that cited DevTreatRules R package
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Other R packages that DevTreatRules depends,
imports, suggests or enhances
Functions, R codes and Examples using
the DevTreatRules R package
Some associated functions: BuildRule . CompareRulesOnValidation . EvaluateRule . PredictRule . SplitData . obsStudyGeneExpressions .
Some associated R codes: BuildRule.R . CompareRulesOnValidation.R . EvaluateRule.R . EvaluateRuleOnce.R . GetComparisonRules.R . Helpers.R . PredictRule.R . RequiredLibraries.R . SplitData.R . data.R . Full DevTreatRules package functions and examples
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