JDSJournal of Data Science1683-86021680-743X1680-743XSchool of Statistics, Renmin University of ChinaJDS1161D10.6339/25-JDS1161DDiscussionDiscussion of “Power Priors for Leveraging Historical Data: Looking Back and Looking Forward”✩ChenFangfangk.chen@sas.com1∗SAS Institute Inc., Cary, NC, USA
Main article: https://doi.org/10.6339/24-JDS1161.
Email: fangk.chen@sas.com.202542202523131372025 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.ReferencesAltEM, ChenX, CarvalhoLM, IbrahimJG (2024). hdbayes: Bayesian Analysis of Generalized Linear Models with Historical Data. R package version 0.1.1. https://CRAN.R-project.org/package=hdbayesChenMH, 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-JDS1161GongY, ChenF (2023). Bayesian models with the power prior using PROC BGLIMM. SAS Statistics Research and Applications Paper 2023-03. SAS Institute Inc., Cary, NC. https://support.sas.com/content/dam/SAS/support/en/technical-papers/bayesian-models-with-the-power-prior-using-proc-bglimm.pdfHoDE, ImaiK, KingG, StuartEA (2011). MatchIt: Nonparametric preprocessing for parametric causal inference. Journal of Statistical Software, 42(8): 1–28. https://doi.org/10.18637/jss.v042.i08IbrahimJG, ChenMH (2000). Power prior distributions for regression models. Statistical Science, 15(1): 46–60. https://doi.org/10.1214/ss/1009212673IbrahimJG, ChenMH, GwonY, ChenF (2015). The power prior: Theory and applications. Statistical Science, 34(28): 3724–3749.SAS Institute Inc (2025). SAS/STAT User’s Guide. SAS Institute Inc., Cary, NC. Revised January 2025. https://documentation.sas.com/doc/en/pgmsascdc/v_059/statug/titlepage.htm