JDSJournal of Data Science1683-86021680-743X1680-743XSchool of Statistics, Renmin University of ChinaJDS1161F10.6339/25-JDS1161FDiscussionDiscussion of “Power Priors for Leveraging Historical Data: Looking Back and Looking Forward”✩WuGuohuigwu03@amgen.com1∗Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA, U.S.A.
Main article: https://doi.org/10.6339/24-JDS1161.
Email: gwu03@amgen.com.202542202523156582025 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2025Open access article under the CC BY license.ReferencesBleiDM, KucukelbirA, McAuliffeJD (2017). Variational inference: A review for statisticians. Journal of the American Statistical Association, 112(518): 859–877. https://doi.org/10.1080/01621459.2017.1285773CarvalhoLM, IbrahimJG (2021). On the normalized power prior. Statistics in Medicine, 40(24): 5251–5275. https://doi.org/10.1002/sim.9124ChenMH, GuanZ, LinM, SunM (2025). Power priors for leveraging historical data: Looking back and looking forward. Journal of Data Science, 23(1): 1–30. https://doi.org/10.6339/24-JDS1161.GravestockI, HeldL (CN Consortium) (2017). Adaptive power priors with empirical Bayes for clinical trials. Pharmaceutical Statistics, 16(5): 349–360. https://doi.org/10.1002/pst.1814HanZ, ZhangQ, WangM, YeK, ChenMH (2023). On efficient posterior inference in normalized power prior Bayesian analysis. Biometrical Journal, 65(5): 2200194. https://doi.org/10.1002/bimj.202200194IbrahimJG, ChenMH (2000). Power prior distributions for regression models. Statistical Science, 15(1): 46–60. https://doi.org/10.1214/ss/1009212673OrmerodJT, WandMP (2010). Explaining variational approximations. American Statistician, 64(2): 140–153. https://doi.org/10.1198/tast.2010.09058PawelS, AustF, HeldL, WagenmakersEJ (2023). Normalized power priors always discount historical data. Stat, 12(1): e591. https://doi.org/10.1002/sta4.591VieleK, BerryS, NeuenschwanderB, AmzalB, ChenF, EnasN, et al. (2014). Use of historical control data for assessing treatment effects in clinical trials. Pharmaceutical Statistics, 13(1): 41–54. https://doi.org/10.1002/pst.1589