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Semiparametric inference of treatment effects on restricted mean survival time in two sample problems from length-biased samples

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  • Yang, Xiaoran
  • Du, Junjie
  • Bai, Fangfang

Abstract

Estimating treatment effects on restricted mean survival time(RMST) is often of direct interest in clinical studies. We propose two approaches based on estimating equation to estimate treatment effects on RMST under the setting of length-biased sampling. The asymptotic properties for the proposed estimators are derived. Simulation studies are performed to evaluate the performance of the methods in finite sample sizes. In addition, we apply our procedures to Oscar Award data.

Suggested Citation

  • Yang, Xiaoran & Du, Junjie & Bai, Fangfang, 2023. "Semiparametric inference of treatment effects on restricted mean survival time in two sample problems from length-biased samples," Statistics & Probability Letters, Elsevier, vol. 193(C).
  • Handle: RePEc:eee:stapro:v:193:y:2023:i:c:s0167715222002280
    DOI: 10.1016/j.spl.2022.109715
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    References listed on IDEAS

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    1. 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.
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    3. Yifan He & Yong Zhou, 2020. "Nonparametric and semiparametric estimators of restricted mean survival time under length-biased sampling," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 761-788, October.
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    5. Lin, Cunjie & Zhou, Yong, 2014. "Inference for the treatment effects in two sample problems with right-censored and length-biased data," Statistics & Probability Letters, Elsevier, vol. 90(C), pages 17-24.
    6. 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.
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