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RobinCar is a package that allows for robust estimation and inference for treatment effects in randomized clinical trials when covariates are used at the design and/or analysis stages of the trial. Supported covariate-adaptive randomization schemes at the design phase are simple randomization, stratified permuted block randomization, biased coin randomization, and Pocock and Simon’s minimization. Statistical methods at the analysis stage are model-assisted and assumption-lean, in accordance with FDA guidance on covariate adjustment. Publications describing the methods are listed here.
See also RobinCar2, which is a lite version of RobinCar and is supported by the ASA Biopharmaceutical Section Covariate Adjustment Scientific Working Group Software Subteam.
Ting Ye, Yanyao Yi, Marlena Bannick (maintainer), Yuhan Qian, and Faith Bian
To view documentation about the functions, see the RobinCar website here: https://marlenabannick.com/RobinCar/. You will also find vignettes about how to use the functions.
RobinCar is now available on CRAN!
install.packages("RobinCar")devtoolsTo get the most recent version in development, you can install the
package with devtools:
devtools::install_github("mbannick/RobinCar")Or to download the package, you may clone the repository:
git clone https://github.com/mbannick/RobinCar.gitHere are publications and preprints that explain the methods in RobinCar:
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.