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A note on semiparametric efficient inference for two-stage outcome-dependent sampling with a continuous outcome

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  • Rui Song
  • Haibo Zhou
  • Michael R. Kosorok

Abstract

Outcome-dependent sampling designs have been shown to be a cost-effective way to enhance study efficiency. We show that the outcome-dependent sampling design with a continuous outcome can be viewed as an extension of the two-stage case-control designs to the continuous-outcome case. We further show that the two-stage outcome-dependent sampling has a natural link with the missing-data and biased-sampling frameworks. Through the use of semiparametric inference and missing-data techniques, we show that a certain semiparametric maximum-likelihood estimator is computationally convenient and achieves the semiparametric efficient information bound. We demonstrate this both theoretically and through simulation. Copyright 2009, Oxford University Press.

Suggested Citation

  • Rui Song & Haibo Zhou & Michael R. Kosorok, 2009. "A note on semiparametric efficient inference for two-stage outcome-dependent sampling with a continuous outcome," Biometrika, Biometrika Trust, vol. 96(1), pages 221-228.
  • Handle: RePEc:oup:biomet:v:96:y:2009:i:1:p:221-228
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    File URL: http://hdl.handle.net/10.1093/biomet/asn073
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    Citations

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    Cited by:

    1. Jieli Ding & Tsui-Shan Lu & Jianwen Cai & Haibo Zhou, 2017. "Recent progresses in outcome-dependent sampling with failure time data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 57-82, January.
    2. Qingning Zhou & Jianwen Cai & Haibo Zhou, 2018. "Outcome†dependent sampling with interval†censored failure time data," Biometrics, The International Biometric Society, vol. 74(1), pages 58-67, March.
    3. Qingning Zhou & Jianwen Cai & Haibo Zhou, 2020. "Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 85-108, January.
    4. Wei-Wen Hsu & David Todem & Kyungmann Kim, 2015. "Adjusted Supremum Score-Type Statistics for Evaluating Non-Standard Hypotheses," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 746-759, September.
    5. Jichang Yu & Haibo Zhou & Jianwen Cai, 2021. "Accelerated failure time model for data from outcome-dependent sampling," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(1), pages 15-37, January.
    6. Xiaofei Wang & Haibo Zhou, 2010. "Design and Inference for Cancer Biomarker Study with an Outcome and Auxiliary-Dependent Subsampling," Biometrics, The International Biometric Society, vol. 66(2), pages 502-511, June.
    7. Haibo Zhou & Rui Song & Yuanshan Wu & Jing Qin, 2011. "Statistical Inference for a Two-Stage Outcome-Dependent Sampling Design with a Continuous Outcome," Biometrics, The International Biometric Society, vol. 67(1), pages 194-202, March.

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