Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing
Publication
, Journal Article
Zhu, K; Yang, S; Wang, X
Published in: Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR
August 1, 2025
Duke Scholars
Published In
Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR
Publication Date
August 1, 2025
Citation
APA
Chicago
ICMJE
MLA
NLM
Zhu, K., Yang, S., & Wang, X. (2025). Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing. Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR.
Zhu, Ke, Shu Yang, and Xiaofei Wang. “Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing.” Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR, August 1, 2025.
Zhu K, Yang S, Wang X. Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing. Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR. 2025 Aug 1;
Zhu, Ke, et al. “Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing.” Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR, Aug. 2025.
Zhu K, Yang S, Wang X. Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing. Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR. 2025 Aug 1;
Published In
Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR
Publication Date
August 1, 2025