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A Bayesian Approach to Surrogacy Assessment Using Principal Stratification in Clinical Trials

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  • Yun Li
  • Jeremy M.G. Taylor
  • Michael R. Elliott

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  • Yun Li & Jeremy M.G. Taylor & Michael R. Elliott, 2010. "A Bayesian Approach to Surrogacy Assessment Using Principal Stratification in Clinical Trials," Biometrics, The International Biometric Society, vol. 66(2), pages 523-531, June.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:2:p:523-531
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01303.x
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    References listed on IDEAS

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    1. Constantine E. Frangakis & Donald B. Rubin, 2002. "Principal Stratification in Causal Inference," Biometrics, The International Biometric Society, vol. 58(1), pages 21-29, March.
    2. Marshall M. Joffe & Tom Greene, 2009. "Related Causal Frameworks for Surrogate Outcomes," Biometrics, The International Biometric Society, vol. 65(2), pages 530-538, June.
    3. Hua Chen & Zhi Geng & Jinzhu Jia, 2007. "Criteria for surrogate end points," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 919-932, November.
    4. VanderWeele, Tyler J., 2008. "Simple relations between principal stratification and direct and indirect effects," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2957-2962, December.
    5. E. S. Venkatraman & Colin B. Begg, 1999. "Properties of A Nonparametric Test for Early Comparison of Treatments in Clinical Trials in the Presence of Surrogate Endpoints," Biometrics, The International Biometric Society, vol. 55(4), pages 1171-1176, December.
    6. Elizabeth S. Garrett & Scott L. Zeger, 2000. "Latent Class Model Diagnosis," Biometrics, The International Biometric Society, vol. 56(4), pages 1055-1067, December.
    7. Paul E. Green & Taesung Park, 2003. "A Bayesian Hierarchical Model for Categorical Data with Nonignorable Nonresponse," Biometrics, The International Biometric Society, vol. 59(4), pages 886-896, December.
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    Citations

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    Cited by:

    1. Rui Zhuang & Ying Qing Chen, 2020. "Measuring Surrogacy in Clinical Research," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 295-323, December.
    2. Michael R. Elliott & Anna Conlon & Yun Li, 2013. "Discussion on “Surrogate Measures and Consistent Surrogates”," Biometrics, The International Biometric Society, vol. 69(3), pages 565-569, September.
    3. Ying Huang & Shibasish Dasgupta, 2019. "Likelihood-Based Methods for Assessing Principal Surrogate Endpoints in Vaccine Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 504-523, December.
    4. Zhichao Jiang & Shu Yang & Peng Ding, 2022. "Multiply robust estimation of causal effects under principal ignorability," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1423-1445, September.
    5. Gilbert Peter B. & Blette Bryan S. & Hudgens Michael G. & Shepherd Bryan E., 2020. "Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 54-69, January.
    6. Corwin M. Zigler & Thomas R. Belin, 2012. "A Bayesian Approach to Improved Estimation of Causal Effect Predictiveness for a Principal Surrogate Endpoint," Biometrics, The International Biometric Society, vol. 68(3), pages 922-932, September.
    7. VanderWeele Tyler J, 2011. "Principal Stratification -- Uses and Limitations," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-14, July.
    8. Debashis Ghosh & Jeremy M. G. Taylor & Daniel J. Sargent, 2012. "Rejoinder for “Meta-analysis for Surrogacy: Accelerated Failure Time Models and Semicompeting Risks Modeling”," Biometrics, The International Biometric Society, vol. 68(1), pages 245-247, March.
    9. Li He & Yu-Bo Wang & William C. Bridges & Zhulin He & S. Megan Che, 2023. "Bayesian Framework for Causal Inference with Principal Stratification and Clusters," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 114-140, April.
    10. Ghosh, Debashis, 2012. "A causal framework for surrogate endpoints with semi-competing risks data," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 1898-1902.
    11. Ariel Alonso & Wim Van der Elst & Geert Molenberghs & Marc Buyse & Tomasz Burzykowski, 2015. "On the relationship between the causal-inference and meta-analytic paradigms for the validation of surrogate endpoints," Biometrics, The International Biometric Society, vol. 71(1), pages 15-24, March.
    12. Ying Huang & Peter B. Gilbert, 2011. "Comparing Biomarkers as Principal Surrogate Endpoints," Biometrics, The International Biometric Society, vol. 67(4), pages 1442-1451, December.
    13. Alessandra Mattei & Fabrizia Mealli & Barbara Pacini, 2014. "Identification of causal effects in the presence of nonignorable missing outcome values," Biometrics, The International Biometric Society, vol. 70(2), pages 278-288, June.
    14. Gilbert Peter B. & Blette Bryan S. & Hudgens Michael G. & Shepherd Bryan E., 2020. "Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 54-69, January.
    15. Ying Huang & Peter B. Gilbert & Julian Wolfson, 2013. "Design and Estimation for Evaluating Principal Surrogate Markers in Vaccine Trials," Biometrics, The International Biometric Society, vol. 69(2), pages 301-309, June.

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