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Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials

Citations

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Cited by:

  1. Hui Quan & Xiaofei Chen & Xun Chen & Xiaodong Luo, 2022. "Assessments of Conditional and Unconditional Type I Error Probabilities for Bayesian Hypothesis Testing with Historical Data Borrowing," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(1), pages 139-157, April.
  2. Chenguang Wang & Min Lin & Gary L. Rosner & Guoxing Soon, 2023. "A Bayesian model with application for adaptive platform trials having temporal changes," Biometrics, The International Biometric Society, vol. 79(2), pages 1446-1458, June.
  3. Stavros Nikolakopoulos & Ingeborg van der Tweel & Kit C. B. Roes, 2018. "Dynamic borrowing through empirical power priors that control type I error," Biometrics, The International Biometric Society, vol. 74(3), pages 874-880, September.
  4. Chenghao Chu & Bingming Yi, 2021. "Dynamic historical data borrowing using weighted average," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1259-1280, November.
  5. Mingyang Shan & Douglas Faries & Andy Dang & Xiang Zhang & Zhanglin Cui & Kristin M. Sheffield, 2022. "A Simulation-Based Evaluation of Statistical Methods for Hybrid Real-World Control Arms in Clinical Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(2), pages 259-284, July.
  6. Andrea Arfè & Brian Alexander & Lorenzo Trippa, 2021. "Optimality of testing procedures for survival data in the nonproportional hazards setting," Biometrics, The International Biometric Society, vol. 77(2), pages 587-598, June.
  7. Thomas A. Murray & Brian P. Hobbs & Theodore C. Lystig & Bradley P. Carlin, 2014. "Semiparametric Bayesian commensurate survival model for post-market medical device surveillance with non-exchangeable historical data," Biometrics, The International Biometric Society, vol. 70(1), pages 185-191, March.
  8. Jing Zhang & Yunzhi Kong & A. John Bailer & Zheng Zhu & Byran Smucker, 2022. "Incorporating Historical Data When Determining Sample Size Requirements for Aquatic Toxicity Experiments," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 544-561, September.
  9. Peng Yang & Yuansong Zhao & Lei Nie & Jonathon Vallejo & Ying Yuan, 2023. "SAM: Self‐adapting mixture prior to dynamically borrow information from historical data in clinical trials," Biometrics, The International Biometric Society, vol. 79(4), pages 2857-2868, December.
  10. Md. Tuhin Sheikh & Ming-Hui Chen & Jonathan A. Gelfond & Joseph G. Ibrahim, 2022. "A Power Prior Approach for Leveraging External Longitudinal and Competing Risks Survival Data Within the Joint Modeling Framework," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(2), pages 318-336, July.
  11. Heinz Schmidli & Sandro Gsteiger & Satrajit Roychoudhury & Anthony O'Hagan & David Spiegelhalter & Beat Neuenschwander, 2014. "Robust meta-analytic-predictive priors in clinical trials with historical control information," Biometrics, The International Biometric Society, vol. 70(4), pages 1023-1032, December.
  12. Arnaud Monseur & Bradley P. Carlin & Bruno Boulanger & Andreea Seferian & Laurent Servais & Chris Freitag & Leen Thielemans, 2022. "Leveraging Natural History Data in One- and Two-Arm Hierarchical Bayesian Studies of Rare Disease Progression," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(2), pages 237-258, July.
  13. David Kaplan & Jianshen Chen & Sinan Yavuz & Weicong Lyu, 2023. "Bayesian Dynamic Borrowing of Historical Information with Applications to the Analysis of Large-Scale Assessments," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 1-30, March.
  14. Chen, Nan & Carlin, Bradley P. & Hobbs, Brian P., 2018. "Web-based statistical tools for the analysis and design of clinical trials that incorporate historical controls," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 50-68.
  15. Ben Li & Yunxiao Li & Zhaohui S. Qin, 2017. "Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 73-90, June.
  16. Jingjing Ye & Gregory Reaman, 2022. "Improving Early Futility Determination by Learning from External Data in Pediatric Cancer Clinical Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(2), pages 337-351, July.
  17. Sidi Wang & Kelley M. Kidwell & Satrajit Roychoudhury, 2023. "Dynamic enrichment of Bayesian small‐sample, sequential, multiple assignment randomized trial design using natural history data: a case study from Duchenne muscular dystrophy," Biometrics, The International Biometric Society, vol. 79(4), pages 3612-3623, December.
  18. Alexander Kaizer & John Kittelson, 2020. "Discussion on “Predictively Consistent Prior Effective Sample Sizes” by Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, and Anthony O'Hagan," Biometrics, The International Biometric Society, vol. 76(2), pages 588-590, June.
  19. Wenlin Yuan & Ming-Hui Chen & John Zhong, 2022. "Flexible Conditional Borrowing Approaches for Leveraging Historical Data in the Bayesian Design of Superiority Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(2), pages 197-215, July.
  20. Yu-Fang Chien & Haiming Zhou & Timothy Hanson & Theodore Lystig, 2023. "Informative g -Priors for Mixed Models," Stats, MDPI, vol. 6(1), pages 1-23, January.
  21. Lanju Zhang & Zailong Wang & Li Wang & Lu Cui & Jeremy Sokolove & Ivan Chan, 2022. "A Simple Approach to Incorporating Historical Control Data in Clinical Trial Design and Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(2), pages 216-236, July.
  22. Liyun Jiang & Lei Nie & Ying Yuan, 2023. "Elastic priors to dynamically borrow information from historical data in clinical trials," Biometrics, The International Biometric Society, vol. 79(1), pages 49-60, March.
  23. Ian Wadsworth & Lisa V. Hampson & Thomas Jaki & Graeme J. Sills & Anthony G. Marson & Richard Appleton, 2020. "A quantitative framework to inform extrapolation decisions in children," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 515-534, February.
  24. Yimei Li & Ying Yuan, 2020. "PA‐CRM: A continuous reassessment method for pediatric phase I oncology trials with concurrent adult trials," Biometrics, The International Biometric Society, vol. 76(4), pages 1364-1373, December.
  25. Moreno Ursino & Nigel Stallard, 2021. "Bayesian Approaches for Confirmatory Trials in Rare Diseases: Opportunities and Challenges," IJERPH, MDPI, vol. 18(3), pages 1-9, January.
  26. Danila Azzolina & Giulia Lorenzoni & Silvia Bressan & Liviana Da Dalt & Ileana Baldi & Dario Gregori, 2021. "Handling Poor Accrual in Pediatric Trials: A Simulation Study Using a Bayesian Approach," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
  27. Chen Li & Haitao Pan, 2020. "A phase I dose-finding design with incorporation of historical information and adaptive shrinking boundaries," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-18, August.
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