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Discussion of “Power Priors for Leveraging Historical Data: Looking Back and Looking Forward”✩
Volume 23, Issue 1 (2025), pp. 38–47
Margaret Gamalo   Heliang Shi   Yuxi Zhao     All authors (4)

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https://doi.org/10.6339/25-JDS1161C
Pub. online: 4 February 2025      Type: Discussion      Open accessOpen Access

✩ Main article: https://doi.org/10.6339/24-JDS1161.

Published
4 February 2025

References

 
Ibrahim JG, Chen M-H (2000). Power prior distributions for regression models. Statistical Science, 15(1): 46–60. https://doi.org/10.1214/ss/1009212673
 
Chen M-H, Guan Z, Lin M, Sun M (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
 
Duan Y, Ye K, Smith EP (2006). Evaluating water quality using power priors to incorporate historical information. Environmetrics: The Official Journal of the International Environmetrics Society, 17(1): 95–106. https://doi.org/10.1002/env.752
 
Bernardo JM (1996). The concept of exchangeability and its applications. Far East Journal of Mathematical Sciences, 4: 111–122.
 
Pawel S, Aust L, Held L, Wagenmakers E-J (2023). Normalized power priors always discount historical data. Stat, 12(1): e591. https://doi.org/10.1002/sta4.591
 
Berger J, Berliner LM (1986). Robust bayes and empirical bayes analysis with ε-contaminated priors. The Annals of Statistics, 14(2): 461–486.
 
Schmidli H, Gsteiger S, Roychoudhury S, O’Hagan A, Spiegelhalter D, Neuenschwander B (2014). Robust meta-analytic-predictive priors in clinical trials with historical control information. Biometrics, 70(4): 1023–1032. https://doi.org/10.1111/biom.12242
 
Izem R, Buenconsejo J, Davi R, Luan JJ, Tracy L, Gamalo M (2022). Real-world data as external controls: practical experience from notable marketing applications of new therapies. Therapeutic Innovation & Regulatory Science, 56(5): 704–716. https://doi.org/10.1007/s43441-022-00413-0
 
Lin J, Gamalo-Siebers M, Tiwari R (2022). Ensuring exchangeability in data-based priors for a bayesian analysis of clinical trials. Pharmaceutical Statistics, 21(2): 327–344. https://doi.org/10.1002/pst.2172
 
Job KM, Gamalo M, Ward RM (2019). Pediatric age groups and approach to studies. Therapeutic Innovation & Regulatory Science, 53(5): 584–589. https://doi.org/10.1177/2168479019856572
 
Gamalo M, Bucci-Rechtweg C, Nelson RM, Vanh L, Porcalla A, Thackray H, et al. (2022). Extrapolation as a default strategy in pediatric drug development. Therapeutic Innovation & Regulatory Science, 56(6): 883–894. https://doi.org/10.1007/s43441-021-00367-9
 
Gamalo MA, Tiwari RC, LaVange LM (2014). Bayesian approach to the design and analysis of non-inferiority trials for anti-infective products. Pharmaceutical Statistics, 13(1): 25–40. https://doi.org/10.1002/pst.1588

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