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Surrogate Measures and Consistent Surrogates

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  • Tyler J. VanderWeele

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  • Tyler J. VanderWeele, 2013. "Surrogate Measures and Consistent Surrogates," Biometrics, The International Biometric Society, vol. 69(3), pages 561-565, September.
  • Handle: RePEc:bla:biomet:v:69:y:2013:i:3:p:561-565
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    File URL: http://hdl.handle.net/10.1111/biom.12071
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    References listed on IDEAS

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    1. Ying Huang & Peter B. Gilbert, 2011. "Comparing Biomarkers as Principal Surrogate Endpoints," Biometrics, The International Biometric Society, vol. 67(4), pages 1442-1451, December.
    2. Constantine E. Frangakis & Donald B. Rubin, 2002. "Principal Stratification in Causal Inference," Biometrics, The International Biometric Society, vol. 58(1), pages 21-29, March.
    3. Chuan Ju & Zhi Geng, 2010. "Criteria for surrogate end points based on causal distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 129-142, January.
    4. Julian Wolfson & Peter Gilbert, 2010. "Statistical Identifiability and the Surrogate Endpoint Problem, with Application to Vaccine Trials," Biometrics, The International Biometric Society, vol. 66(4), pages 1153-1161, December.
    5. Marshall M. Joffe & Tom Greene, 2009. "Related Causal Frameworks for Surrogate Outcomes," Biometrics, The International Biometric Society, vol. 65(2), pages 530-538, June.
    6. 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.
    7. Peter B. Gilbert & Michael G. Hudgens, 2008. "Evaluating Candidate Principal Surrogate Endpoints," Biometrics, The International Biometric Society, vol. 64(4), pages 1146-1154, December.
    8. Steffen L. Lauritzen, 2004. "Discussion on Causality," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(2), pages 189-193, June.
    9. Dean Follmann, 2006. "Augmented Designs to Assess Immune Response in Vaccine Trials," Biometrics, The International Biometric Society, vol. 62(4), pages 1161-1169, December.
    10. Tyler J. VanderWeele & James M. Robins, 2010. "Signed directed acyclic graphs for causal inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 111-127, January.
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    Citations

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    Cited by:

    1. Gilbert Peter B. & Huang Ying & Gabriel Erin E. & Chan Ivan S.F., 2015. "Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition," Journal of Causal Inference, De Gruyter, vol. 3(2), pages 157-175, September.
    2. 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.
    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. Guido Imbens & Nathan Kallus & Xiaojie Mao & Yuhao Wang, 2022. "Long-term Causal Inference Under Persistent Confounding via Data Combination," Papers 2202.07234, arXiv.org, revised Aug 2023.
    5. 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.
    6. 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.
    7. 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.
    8. Fatema Shafie Khorassani & Jeremy M. G. Taylor & Niko Kaciroti & Michael R. Elliott, 2023. "Incorporating Covariates into Measures of Surrogate Paradox Risk," Stats, MDPI, vol. 6(1), pages 1-23, February.
    9. Hema Yoganarasimhan & Ebrahim Barzegary & Abhishek Pani, 2023. "Design and Evaluation of Optimal Free Trials," Management Science, INFORMS, vol. 69(6), pages 3220-3240, June.
    10. Zhichao Jiang & Peng Ding & Zhi Geng, 2016. "Principal causal effect identification and surrogate end point evaluation by multiple trials," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 829-848, September.
    11. Denis Agniel & Layla Parast, 2021. "Evaluation of longitudinal surrogate markers," Biometrics, The International Biometric Society, vol. 77(2), pages 477-489, June.
    12. Yechan Park & Yuya Sasaki, 2024. "A Bracketing Relationship for Long-Term Policy Evaluation with Combined Experimental and Observational Data," Papers 2401.12050, arXiv.org.
    13. Emily K. Roberts & Michael R. Elliott & Jeremy M. G. Taylor, 2023. "Solutions for surrogacy validation with longitudinal outcomes for a gene therapy," Biometrics, The International Biometric Society, vol. 79(3), pages 1840-1852, September.
    14. Carlos Fernández-Loría & Foster Provost, 2022. "Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 4-16, April.
    15. 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.

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