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fdb  

Frequentist Dynamic Borrowing for Hybrid-Control Survival Trials
View on CRAN: Click here


Download and install fdb package within the R console
Install from CRAN:
install.packages("fdb")

Install from Github:
library("remotes")
install_github("cran/fdb")

Install by package version:
library("remotes")
install_version("fdb", "0.2.0")



Attach the package and use:
library("fdb")
Maintained by
Yusuke Yamaguchi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-10-04
Latest Update: 2026-10-04
Description:
Implements a class of likelihood-informed frequentist dynamic borrowing methods for hybrid-control survival trials based on penalized Cox partial likelihood estimation. Implements four likelihood-informed penalty structures (precision-weighted L1, smoothed integrated-gate, information-adaptive minimax concave penalty (MCP), and likelihood-ratio-weighted L1), together with the adaptive lasso borrowing approach of Li et al. (2023, <doi:10.1002/bimj.202100406>). Provides conditional model-based standard errors and local plug-in sandwich variance approximations, with smoothed penalties. Tools for design-stage lambda calibration via simulation, including a two-stage coarse-fine grid search, drift-level early stopping, and per-method tuning under both inference types, are also provided. A simulation harness for evaluating type I error and statistical power across population drift scenarios is included.
How to cite:
Yusuke Yamaguchi (2026). fdb: Frequentist Dynamic Borrowing for Hybrid-Control Survival Trials. R package version 0.2.0, https://cran.r-project.org/web/packages/fdb. Accessed 25 Oct. 2026.
Previous versions and publish date:
(2026-10-10 17:50), 0.2.0 (2026-10-04 11:20)
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