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Causal Inference on the Difference of the Restricted Mean Lifetime Between Two Groups

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  • Pei-Yun Chen
  • Anastasios A. Tsiatis

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  • Pei-Yun Chen & Anastasios A. Tsiatis, 2001. "Causal Inference on the Difference of the Restricted Mean Lifetime Between Two Groups," Biometrics, The International Biometric Society, vol. 57(4), pages 1030-1038, December.
    • Handle: RePEc:bla:biomet:v:57:y:2001:i:4:p:1030-1038
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2001.01030.x
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    Cited by:

    1. Shu Yang & Yilong Zhang & Guanghan Frank Liu & Qian Guan, 2023. "SMIM: A unified framework of survival sensitivity analysis using multiple imputation and martingale," Biometrics, The International Biometric Society, vol. 79(1), pages 230-240, March.
    2. Yasuhiro Hagiwara & Tomohiro Shinozaki & Yutaka Matsuyama, 2020. "G‐estimation of structural nested restricted mean time lost models to estimate effects of time‐varying treatments on a failure time outcome," Biometrics, The International Biometric Society, vol. 76(3), pages 799-810, September.
    3. Ruosha Li & Limin Peng, 2017. "Assessing quantile prediction with censored quantile regression models," Biometrics, The International Biometric Society, vol. 73(2), pages 517-528, June.
    4. Min Zhang & Douglas E. Schaubel, 2012. "Double-Robust Semiparametric Estimator for Differences in Restricted Mean Lifetimes in Observational Studies," Biometrics, The International Biometric Society, vol. 68(4), pages 999-1009, December.
    5. Qi Gong & Douglas E. Schaubel, 2017. "Estimating the average treatment effect on survival based on observational data and using partly conditional modeling," Biometrics, The International Biometric Society, vol. 73(1), pages 134-144, March.
    6. Chi Hyun Lee & Jing Ning & Yu Shen, 2018. "Analysis of restricted mean survival time for length†biased data," Biometrics, The International Biometric Society, vol. 74(2), pages 575-583, June.
    7. Ran Dai & Cheng Zheng & Mei-Jie Zhang, 2023. "On High-Dimensional Covariate Adjustment for Estimating Causal Effects in Randomized Trials with Survival Outcomes," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 242-260, April.
    8. Min Zhang & Douglas E. Schaubel, 2011. "Estimating Differences in Restricted Mean Lifetime Using Observational Data Subject to Dependent Censoring," Biometrics, The International Biometric Society, vol. 67(3), pages 740-749, September.
    9. Adin-Cristian Andrei & Susan Murray, 2007. "Regression Models for the Mean of the Quality-of-Life-Adjusted Restricted Survival Time Using Pseudo-Observations," Biometrics, The International Biometric Society, vol. 63(2), pages 398-404, June.
    10. Zahra Mansourvar & Torben Martinussen, 2017. "Estimation of average causal effect using the restricted mean residual lifetime as effect measure," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 426-438, July.
    11. Iván Díaz & Elizabeth Colantuoni & Daniel F. Hanley & Michael Rosenblum, 2019. "Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 439-468, July.
    12. Layla Parast & Beth Ann Griffin, 2017. "Landmark estimation of survival and treatment effects in observational studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 161-182, April.
    13. Yu-Jen Cheng & Mei-Cheng Wang, 2015. "Causal estimation using semiparametric transformation models under prevalent sampling," Biometrics, The International Biometric Society, vol. 71(2), pages 302-312, June.
    14. Lu Mao, 2023. "On restricted mean time in favor of treatment," Biometrics, The International Biometric Society, vol. 79(1), pages 61-72, March.
    15. Santiago Acerenza & Vitor Possebom & Pedro H. C. Sant'Anna, 2023. "Was Javert right to be suspicious? Unpacking treatment effect heterogeneity of alternative sentences on time-to-recidivism in Brazil," Papers 2311.13969, arXiv.org, revised Jan 2024.
    16. Rui Song & Michael R. Kosorok & Jianwen Cai, 2008. "Robust Covariate‐Adjusted Log‐Rank Statistics and Corresponding Sample Size Formula for Recurrent Events Data," Biometrics, The International Biometric Society, vol. 64(3), pages 741-750, September.
    17. Yingchao Zhong & Douglas E. Schaubel, 2022. "Restricted mean survival time as a function of restriction time," Biometrics, The International Biometric Society, vol. 78(1), pages 192-201, March.
    18. David Benkeser & Iván Díaz & Alex Luedtke & Jodi Segal & Daniel Scharfstein & Michael Rosenblum, 2021. "Improving precision and power in randomized trials for COVID‐19 treatments using covariate adjustment, for binary, ordinal, and time‐to‐event outcomes," Biometrics, The International Biometric Society, vol. 77(4), pages 1467-1481, December.
    19. Xin Wang & Douglas E. Schaubel, 2018. "Modeling restricted mean survival time under general censoring mechanisms," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 176-199, January.
    20. Douglas E. Schaubel & Guanghui Wei, 2011. "Double Inverse-Weighted Estimation of Cumulative Treatment Effects Under Nonproportional Hazards and Dependent Censoring," Biometrics, The International Biometric Society, vol. 67(1), pages 29-38, March.
    21. Nicholas Williams & Michael Rosenblum & Iván Díaz, 2022. "Optimising precision and power by machine learning in randomised trials with ordinal and time‐to‐event outcomes with an application to COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2156-2178, October.
    22. Jiyang Wen & Chen Hu & Mei‐Cheng Wang, 2023. "Joint inference for competing risks data using multiple endpoints," Biometrics, The International Biometric Society, vol. 79(3), pages 1635-1645, September.
    23. Kaeding, Matthias, 2020. "Efficient Bayesian nonparametric hazard regression," Ruhr Economic Papers 850, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    24. 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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