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A Measure of the Proportion of Treatment Effect Explained by a Surrogate Marker

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  • Yue Wang
  • Jeremy M. G. Taylor

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  • Yue Wang & Jeremy M. G. Taylor, 2002. "A Measure of the Proportion of Treatment Effect Explained by a Surrogate Marker," Biometrics, The International Biometric Society, vol. 58(4), pages 803-812, December.
  • Handle: RePEc:bla:biomet:v:58:y:2002:i:4:p:803-812
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00803.x
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    Citations

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    Cited by:

    1. Cheng Zheng & Lei Liu, 2022. "Quantifying direct and indirect effect for longitudinal mediator and survival outcome using joint modeling approach," Biometrics, The International Biometric Society, vol. 78(3), pages 1233-1243, September.
    2. Debashis Ghosh & Jeremy M. G. Taylor & Daniel J. Sargent, 2012. "Meta-analysis for Surrogacy: Accelerated Failure Time Models and Semicompeting Risks Modeling," Biometrics, The International Biometric Society, vol. 68(1), pages 226-232, March.
    3. 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.
    4. Layla Parast & Lu Tian & Tianxi Cai, 2020. "Assessing the value of a censored surrogate outcome," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 245-265, April.
    5. Rui Zhuang & Fan Xia & Yixin Wang & Ying-Qing Chen, 2022. "A Surrogate Measure for Time-Varying Biomarkers in Randomized Clinical Trials," Mathematics, MDPI, vol. 10(4), pages 1-17, February.
    6. Manabu Kuroki, 2016. "The Identification of Direct and Indirect Effects in Studies with an Unmeasured Intermediate Variable," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 228-245, March.
    7. Layla Parast & Tianxi Cai & Lu Tian, 2023. "Testing for heterogeneity in the utility of a surrogate marker," Biometrics, The International Biometric Society, vol. 79(2), pages 799-810, June.
    8. Layla Parast & Tanya P. Garcia & Ross L. Prentice & Raymond J. Carroll, 2022. "Robust methods to correct for measurement error when evaluating a surrogate marker," Biometrics, The International Biometric Society, vol. 78(1), pages 9-23, March.
    9. Xuan Wang & Layla Parast & Larry Han & Lu Tian & Tianxi Cai, 2023. "Robust approach to combining multiple markers to improve surrogacy," Biometrics, The International Biometric Society, vol. 79(2), pages 788-798, June.
    10. Steffen Mickenautsch & Veerasamy Yengopal, 2013. "Validity of Sealant Retention as Surrogate for Caries Prevention – A Systematic Review," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-9, October.
    11. Debashis Ghosh, 2009. "On Assessing Surrogacy in a Single Trial Setting Using a Semicompeting Risks Paradigm," Biometrics, The International Biometric Society, vol. 65(2), pages 521-529, June.
    12. Jeremy M. G. Taylor & Yue Wang & Rodolphe Thiébaut, 2005. "Counterfactual Links to the Proportion of Treatment Effect Explained by a Surrogate Marker," Biometrics, The International Biometric Society, vol. 61(4), pages 1102-1111, December.
    13. 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.
    14. Denis Agniel & Layla Parast, 2021. "Evaluation of longitudinal surrogate markers," Biometrics, The International Biometric Society, vol. 77(2), pages 477-489, June.
    15. John O'Quigley & Philippe Flandre, 2012. "Discussion by O'Quigley and Flandre," Biometrics, The International Biometric Society, vol. 68(1), pages 242-244, March.
    16. Yun Li & Jeremy M. G. Taylor & Roderick J. A. Little, 2011. "A Shrinkage Approach for Estimating a Treatment Effect Using Intermediate Biomarker Data in Clinical Trials," Biometrics, The International Biometric Society, vol. 67(4), pages 1434-1441, December.
    17. Zhihong Cai & Manabu Kuroki & Judea Pearl & Jin Tian, 2008. "Bounds on Direct Effects in the Presence of Confounded Intermediate Variables," Biometrics, The International Biometric Society, vol. 64(3), pages 695-701, September.
    18. Debashis Ghosh, 2008. "Semiparametric Inference for Surrogate Endpoints with Bivariate Censored Data," Biometrics, The International Biometric Society, vol. 64(1), pages 149-156, March.
    19. Layla Parast & Tianxi Cai & Lu Tian, 2021. "Evaluating multiple surrogate markers with censored data," Biometrics, The International Biometric Society, vol. 77(4), pages 1315-1327, December.
    20. 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.
    21. Banerjee, Buddhananda & Biswas, Atanu, 2015. "Linear increment in efficiency with the inclusion of surrogate endpoint," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 102-108.

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