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Cause-Specific Cumulative Incidence Estimation and the Fine and Gray Model Under Both Left Truncation and Right Censoring

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  • Ronald B. Geskus

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  • Ronald B. Geskus, 2011. "Cause-Specific Cumulative Incidence Estimation and the Fine and Gray Model Under Both Left Truncation and Right Censoring," Biometrics, The International Biometric Society, vol. 67(1), pages 39-49, March.
    • Handle: RePEc:bla:biomet:v:67:y:2011:i:1:p:39-49
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01420.x
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    Citations

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    Cited by:

    1. Erik T. Parner & Per K. Andersen & Morten Overgaard, 2023. "Regression models for censored time-to-event data using infinitesimal jack-knife pseudo-observations, with applications to left-truncation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(3), pages 654-671, July.
    2. Xiaomeng Qi & Zhangsheng Yu, 2023. "Kernel regression for cause-specific hazard models with time-dependent coefficients," Computational Statistics, Springer, vol. 38(1), pages 263-283, March.
    3. Deresa, Negera Wakgari & Van Keilegom, Ingrid, 2020. "A multivariate normal regression model for survival data subject to different types of dependent censoring," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    4. repec:jss:jstsof:43:i13 is not listed on IDEAS
    5. Pavlova, Elitsa & Signore, Simone, 2021. "The European venture capital landscape: An EIF perspective. Volume VI: The impact of VC on the exit and innovation outcomes of EIF-backed start-ups," EIF Working Paper Series 2021/70, European Investment Fund (EIF).
    6. Soyoung Kim & Yayun Xu & Mei‐Jie Zhang & Kwang‐Woo Ahn, 2020. "Stratified proportional subdistribution hazards model with covariate‐adjusted censoring weight for case‐cohort studies," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1222-1242, December.
    7. Zhang, Feipeng & Peng, Heng & Zhou, Yong, 2016. "Composite partial likelihood estimation for length-biased and right-censored data with competing risks," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 160-176.
    8. Zhang, Qiaozhen & Dai, Hongsheng & Fu, Bo, 2016. "A proportional hazards model for time-to-event data with epidemiological bias," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 224-236.
    9. Jackson P. Lautier & Vladimir Pozdnyakov & Jun Yan, 2022. "On the Convergence of Credit Risk in Current Consumer Automobile Loans," Papers 2211.09176, arXiv.org, revised Jan 2024.
    10. Qing Liu & Gong Tang & Joseph P. Costantino & Chung‐Chou H. Chang, 2020. "Landmark proportional subdistribution hazards models for dynamic prediction of cumulative incidence functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1145-1162, November.
    11. Vanessa di Lego & Cássio M. Turra & Cibele Cesar, 2017. "Mortality selection among adults in Brazil: The survival advantage of Air Force officers," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(41), pages 1339-1350.
    12. Li, Ruosha & Peng, Limin, 2014. "Varying coefficient subdistribution regression for left-truncated semi-competing risks data," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 65-78.
    13. Yuxue Jin & Tze Leung Lai, 2017. "A new approach to regression analysis of censored competing-risks data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(4), pages 605-625, October.

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