InfluenceBorrowing
Adaptive Influence-Based Borrowing for Hybrid Control Trials
Implements the adaptive influence-based borrowing framework proposed by Qinwei Yang, Jingyi Li, Peng Wu, and Shu Yang (2026+) in the paper ``Improving Treatment Effect Estimation in Trials through Adaptive Borrowing of External Controls" <doi:10.48550/arXiv.2604.13973> for augmenting Randomized Controlled Trials (RCTs) with External Control (EC) data. This package provides a comprehensive workflow to: (1) quantify the comparability of external control samples using influence scores approximated via the influence function of the M-estimator; (2) construct candidate borrowing subsets and select the optimal subset that minimizes the Mean Squared Error (MSE); and (3) calibrate systematic differences in external outcomes using R-learner methods implemented via Ordinary Least Squares or Kernel Ridge Regression.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | InfluenceBorrowing_0.1.0.tar.gz |
57.0 KiB |
0.1.0 |
rolling linux/noble R-4.5 | InfluenceBorrowing_0.1.0.tar.gz |
56.9 KiB |
0.1.0 |
rolling source/ R- | InfluenceBorrowing_0.1.0.tar.gz |
12.5 KiB |
0.1.0 |
latest linux/jammy R-4.5 | InfluenceBorrowing_0.1.0.tar.gz |
57.0 KiB |
0.1.0 |
latest linux/noble R-4.5 | InfluenceBorrowing_0.1.0.tar.gz |
56.9 KiB |
0.1.0 |
latest source/ R- | InfluenceBorrowing_0.1.0.tar.gz |
12.5 KiB |
0.1.0 |
2026-04-26 source/ R- | InfluenceBorrowing_0.1.0.tar.gz |
12.5 KiB |
0.1.0 |
2026-04-23 source/ R- | InfluenceBorrowing_0.1.0.tar.gz |
0 B |