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Rejoinder: “Power Priors for Leveraging Historical Data: Looking Back and Looking Forward”,✩✩,✩
Volume 23, Issue 1 (2025), pp. 64–69
Ming-Hui Chen   Zhe Guan   Min Lin     All authors (4)

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https://doi.org/10.6339/25-JDS1172
Pub. online: 4 February 2025      Type: Statistical Data Science      Open accessOpen Access

✩✩ Main article: https://doi.org/10.6339/24-JDS1161.
✩ Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Received
25 January 2025
Accepted
28 January 2025
Published
4 February 2025

References

 
Baron E, Lin M, Zhu J, Tang RS, Chen MH (2024). Enhancing randomized controlled trials: A Bayesian divide-and-conquer approach for borrowing external control data. Statistics in Biosciences, https://doi.org/10.1007/s12561-024-09465-2.
 
Best N, Price RG, Pouliquen IJ, Keene ON (2021). Assessing efficacy in important subgroups in confirmatory trials: An example using Bayesian dynamic borrowing. Pharmaceutical Statistics, 20(3): 551–562. https://doi.org/10.1002/pst.2093
 
Blei DM, Kucukelbir A, McAuliffe JD (2017). Variational inference: A review for statisticians. Journal of the American Statistical Association, 112(518): 859–877. https://doi.org/10.1080/01621459.2017.1285773
 
Chen MH, 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
 
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
 
Simpson EH (1951). The interpretation of interaction in contingency tables. Journal of the Royal Statistical Society, Series B (Methodological), 13(2): 238–241. https://doi.org/10.1111/j.2517-6161.1951.tb00088.x
 
Xie M, Liu RY, Damaraju CV, Olson WH (2013). Incorporating external information in analyses of clinical trials with binary outcomes. Annals of Applied Statistics, 7(1): 342–368. https://doi.org/10.1214/12-AOAS585

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2025 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.
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