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rdborrow
View on CRAN: Click
here
Download and install rdborrow package within the R console
Install from CRAN:
install.packages("rdborrow")
Install from Github:
library("remotes")
install_github("cran/rdborrow") Install by package version:
library("remotes")
install_version("rdborrow", "0.0.4.0") Attach the package and use:
library("rdborrow")
Maintained by
Matt Secrest
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
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First Published: 2026-08-31
Latest Update: 2026-08-31
Description:
Implements causal inference methods for incorporating external control data into randomized controlled trials (RCTs) with longitudinal outcomes. Provides an analysis module supporting weighting-based methods such as inverse probability weighting (IPW) and augmented inverse probability weighting (AIPW), difference-in-differences (DID), and synthetic control approaches for borrowing external control information, as well as a simulation module for generating trial and external control data, evaluating estimator performance via Monte Carlo studies, and conducting power analyses for sample size determination. Methods are based on Zhou et al. (2024) <doi:10.1093/biostatistics/kxae012> and Zhou et al. (2024) <doi:10.1080/01621459.2024.2395586>.
How to cite:
Matt Secrest (2026). rdborrow: External Control Borrowing for Rare Disease Trials. R package version 0.0.4.0, https://cran.r-project.org/web/packages/rdborrow. Accessed 20 Sep. 2026.
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