Bayesian adaptive enrichment design in multi-arm clinical trials: The BayesAET package for R users
BayesAET provides a comprehensive tool for designing and analyzing Bayesian adaptive enrichment trials to identify the optimal treatments with pre-specified subpopulations.
Authors
- Hubert Wong (ORCID: https://orcid.org/0000-0001-8840-4509)
- Fidel Vila‐Rodriguez (ORCID: https://orcid.org/0000-0002-8273-8820)
- Mohammad Ehsanul Karim (ORCID: https://orcid.org/0000-0002-0346-2871)
- Denghuang Zhan (ORCID: https://orcid.org/0000-0002-8667-6460)
- Yongdong Ouyang (ORCID: https://orcid.org/0000-0002-8692-2991)
Institutions
- University of British Columbia (CA)
- University of Toronto (CA)
- Hospital for Sick Children (CA)
- Public Health Ontario (CA)
- St. Paul's Hospital (CA)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1016/j.cmpb.2025.108833
- Citations
- 1
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 2.63
Funders
- Alliance de recherche numérique du Canada
- Canadian Institutes of Health Research