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Inference in randomized trials with death and missingness

Author

Listed:
  • Chenguang Wang
  • Daniel O. Scharfstein
  • Elizabeth Colantuoni
  • Timothy D. Girard
  • Ying Yan

Abstract

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Suggested Citation

  • Chenguang Wang & Daniel O. Scharfstein & Elizabeth Colantuoni & Timothy D. Girard & Ying Yan, 2017. "Inference in randomized trials with death and missingness," Biometrics, The International Biometric Society, vol. 73(2), pages 431-440, June.
    • Handle: RePEc:bla:biomet:v:73:y:2017:i:2:p:431-440
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    File URL: http://hdl.handle.net/10.1111/biom.12594
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    Citations

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    Cited by:

    1. Daniel Commenges, 2019. "Dealing with death when studying disease or physiological marker: the stochastic system approach to causality," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 381-405, July.
    2. Maria Josefsson & Michael J. Daniels, 2021. "Bayesian semi‐parametric G‐computation for causal inference in a cohort study with MNAR dropout and death," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 398-414, March.
    3. Zhiwei Zhang & Wei Li & Hui Zhang, 2020. "Efficient Estimation of Mann–Whitney-Type Effect Measures for Right-Censored Survival Outcomes in Randomized Clinical Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 246-262, July.

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