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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "InfluenceBorrowing" in publications use:'
type: software
license: GPL-3.0-only
title: 'InfluenceBorrowing: Adaptive Influence-Based Borrowing for Hybrid Control
  Trials'
version: 0.1.0
doi: 10.32614/CRAN.package.InfluenceBorrowing
abstract: '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" <https://doi.org/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.'
authors:
- family-names: Chaoge
  given-names: Jile
  email: chogjill@126.com
- family-names: Wu
  given-names: Peng
- family-names: Yang
  given-names: Shu
repository: https://jilechaoge.r-universe.dev
commit: 7edef2b74333966799ea405ff1bcb6f153b62245
date-released: '2026-04-23'
contact:
- family-names: Chaoge
  given-names: Jile
  email: chogjill@126.com