Empirical bayes approach for dynamic bayesian borrowing for clinical trials in rare diseases
Author:
Publisher
Springer Science and Business Media LLC
Subject
Pharmacology
Link
https://link.springer.com/content/pdf/10.1007/s10928-023-09860-0.pdf
Reference7 articles.
1. Liu J, Barrett JS, Leonardi ET, Lee L, Roychoudhury S, Chen Y, Panayiota Trifillis P (2022) Natural history and Real-World Data in Rare Diseases: applications, Limitations, and future perspectives. J Clin Pharmacol 62(S2):38–S5. https://doi.org/10.1002/jcph.2134
2. Chen M-H, Ibrahim J (2000) Power prior distributions for regression models. Stat Sci 15(1):46–60. https://doi.org/10.1214/ss/1009212673
3. Gajewski BJ, Reese CS, Colombo J, Carlson SE (2016) Commensurate Priors on a Finite Mixture Model for Incorporating Repository Data in Clinical Trials. Statistics in Biopharmaceutical Research Volume 8, 151–160. https://doi.org/10.1080/19466315.2015.1133453 Psioda M and Xueb X, 2020. A Bayesian Adaptive Two-Stage Design for Pediatric Clinical Trials. Journal of Biopharmaceutical Statistics 30 (6), 1091–1108 https://doi.org/10.1080/10543406.2020.1821704
4. Depaoli S, Yang Y, Felt J (2017) Using bayesian statistics to model uncertainty in mixture models: a sensitivity analysis of Priors. Struct Equ Model Volume 24(Issue 2):198–215. https://doi.org/10.1080/10705511.2016.1250640
5. Wakefield J, De Vocht F, Hung RJ (2010) Bayesian mixture modeling of gene-environment and gene-gene interactions. Genet Epidemiol 34:16–25. https://doi.org/10.1002/gepi.20429
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