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Generalized case–cohort sampling

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  • Kani Chen

Abstract

A class of cohort sampling designs, including nested case–control, case–cohort and classical case–control designs involving survival data, is studied through a unified approach using Cox’s proportional hazards model. By finding an optimal sample reuse method via local averaging, a closed form estimating function is obtained, leading directly to the estimators of the regression parameters that are relatively easy to compute and are more efficient than some commonly used estimators in case–cohort and nested case–control studies. A semiparametric efficient estimator can also be found with some further computation. In addition, the class of sampling designs in this study provides a variety of sampling options and relaxes the restrictions of sampling schemes that are currently available.

Suggested Citation

  • Kani Chen, 2001. "Generalized case–cohort sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 791-809.
    • Handle: RePEc:bla:jorssb:v:63:y:2001:i:4:p:791-809
    DOI: 10.1111/1467-9868.00313
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    Cited by:

    1. Ying Yan & Haibo Zhou & Jianwen Cai, 2017. "Improving efficiency of parameter estimation in case-cohort studies with multivariate failure time data," Biometrics, The International Biometric Society, vol. 73(3), pages 1042-1052, September.
    2. Guangren Yang & Yanqing Sun & Li Qi & Peter B. Gilbert, 2017. "Estimation of Stratified Mark-Specific Proportional Hazards Models Under Two-Phase Sampling with Application to HIV Vaccine Efficacy Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 259-283, June.
    3. Erik T. Parner & Per K. Andersen & Morten Overgaard, 2020. "Cumulative risk regression in case–cohort studies using pseudo-observations," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 639-658, October.
    4. Lin, Chanjuan & Zheng, Ming & Yu, Wen & Wu, Mingzhe, 2019. "Robust inference for the proportional hazards model with two-phase cohort sampling data," Statistics & Probability Letters, Elsevier, vol. 153(C), pages 98-103.
    5. Gongjun Xu & Tony Sit & Lan Wang & Chiung-Yu Huang, 2017. "Estimation and Inference of Quantile Regression for Survival Data Under Biased Sampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1571-1586, October.
    6. Jing Zhang & Haibo Zhou & Yanyan Liu & Jianwen Cai, 2021. "Conditional screening for ultrahigh-dimensional survival data in case-cohort studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(4), pages 632-661, October.
    7. Sangwook Kang & Jianwen Cai, 2009. "Marginal Hazards Regression for Retrospective Studies within Cohort with Possibly Correlated Failure Time Data," Biometrics, The International Biometric Society, vol. 65(2), pages 405-414, June.
    8. Yanqing Sun & Xiyuan Qian & Qiong Shou & Peter B. Gilbert, 2017. "Analysis of two-phase sampling data with semiparametric additive hazards models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 377-399, July.
    9. E. Vittinghoff & D. C. Bauer, 2006. "Case-Only Analysis of Treatment–Covariate Interactions in Clinical Trials," Biometrics, The International Biometric Society, vol. 62(3), pages 769-776, September.
    10. Poulami Maitra & Leila D. A. F. Amorim & Jianwen Cai, 2020. "Multiplicative rates model for recurrent events in case-cohort studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 134-157, January.
    11. Hui Zhang & Douglas E. Schaubel & John D. Kalbfleisch, 2011. "Proportional Hazards Regression for the Analysis of Clustered Survival Data from Case–Cohort Studies," Biometrics, The International Biometric Society, vol. 67(1), pages 18-28, March.
    12. Mingzhe Wu & Ming Zheng & Wen Yu & Ruofan Wu, 2018. "Estimation and variable selection for semiparametric transformation models under a more efficient cohort sampling design," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 570-596, September.
    13. 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.
    14. Jie-Huei Wang & Chun-Hao Pan & I-Shou Chang & Chao Agnes Hsiung, 2020. "Penalized full likelihood approach to variable selection for Cox’s regression model under nested case–control sampling," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 292-314, April.
    15. Zheng, Ming & Zhao, Ziqiang & Yu, Wen, 2013. "Quantile regression analysis of case-cohort data," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 20-34.

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