IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v68y2012i2p637-647.html
   My bibliography  Save this article

Computationally Efficient Marginal Models for Clustered Recurrent Event Data

Author

Listed:
  • Dandan Liu
  • Douglas E. Schaubel
  • John D. Kalbfleisch

Abstract

No abstract is available for this item.

Suggested Citation

  • Dandan Liu & Douglas E. Schaubel & John D. Kalbfleisch, 2012. "Computationally Efficient Marginal Models for Clustered Recurrent Event Data," Biometrics, The International Biometric Society, vol. 68(2), pages 637-647, June.
    • Handle: RePEc:bla:biomet:v:68:y:2012:i:2:p:637-647
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2011.01676.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yining Ye & John D. Kalbfleisch & Douglas E. Schaubel, 2007. "Semiparametric Analysis of Correlated Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 63(1), pages 78-87, March.
    2. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    3. J. Sun & L. J. Wei, 2000. "Regression analysis of panel count data with covariate‐dependent observation and censoring times," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 293-302.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marie Böhnstedt & Jutta Gampe & Monique A. A. Caljouw & Hein Putter, 2023. "Incorporating delayed entry into the joint frailty model for recurrent events and a terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(3), pages 585-607, July.
    2. Kang Fang Yuan, 2018. "The Model and the Inference for the Clustered Recurrent Event," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 5(4), pages 106-107, February.
    3. He, Haijin & Pan, Deng & Sun, Liuquan & Li, Yimei & Robison, Leslie L. & Song, Xinyuan, 2017. "Analysis of a fixed center effect additive rates model for recurrent event data," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 186-197.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jie Zhou & Haixiang Zhang & Liuquan Sun & Jianguo Sun, 2017. "Joint analysis of panel count data with an informative observation process and a dependent terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(4), pages 560-584, October.
    2. Xingqiu Zhao & Jie Zhou & Liuquan Sun, 2011. "Semiparametric Transformation Models with Time-Varying Coefficients for Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 67(2), pages 404-414, June.
    3. Hui Zhao & Yang Li & Jianguo Sun, 2013. "Semiparametric analysis of multivariate panel count data with dependent observation processes and a terminal event," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 379-394, June.
    4. Na Cai & Wenbin Lu & Hao Helen Zhang, 2012. "Time-Varying Latent Effect Model for Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 68(4), pages 1093-1102, December.
    5. Xiaowei Sun & Jieli Ding & Liuquan Sun, 2020. "A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 471-492, July.
    6. Xiaoyu Wang & Liuquan Sun, 2023. "Joint modeling of generalized scale-change models for recurrent event and failure time data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 1-33, January.
    7. Qing Pan & Douglas E. Schaubel, 2009. "Flexible Estimation of Differences in Treatment-Specific Recurrent Event Means in the Presence of a Terminating Event," Biometrics, The International Biometric Society, vol. 65(3), pages 753-761, September.
    8. Miao Han & Liuquan Sun & Yutao Liu & Jun Zhu, 2018. "Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(5), pages 523-547, July.
    9. Tianmeng Lyu & Björn Bornkamp & Guenther Mueller‐Velten & Heinz Schmidli, 2023. "Bayesian inference for a principal stratum estimand on recurrent events truncated by death," Biometrics, The International Biometric Society, vol. 79(4), pages 3792-3802, December.
    10. C.-Y. Huang & J. Qin & M.-C. Wang, 2010. "Semiparametric Analysis for Recurrent Event Data with Time-Dependent Covariates and Informative Censoring," Biometrics, The International Biometric Society, vol. 66(1), pages 39-49, March.
    11. Jianguo Sun & Xingwei Tong & Xin He, 2007. "Regression Analysis of Panel Count Data with Dependent Observation Times," Biometrics, The International Biometric Society, vol. 63(4), pages 1053-1059, December.
    12. Gang Cheng & Ying Zhang & Liqiang Lu, 2011. "Efficient algorithms for computing the non and semi-parametric maximum likelihood estimates with panel count data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 567-579.
    13. Li, Yang & Zhao, Hui & Sun, Jianguo & Kim, KyungMann, 2014. "Nonparametric tests for panel count data with unequal observation processes," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 103-111.
    14. Kwun Chuen Gary Chan & Mei-Cheng Wang, 2017. "Semiparametric Modeling and Estimation of the Terminal Behavior of Recurrent Marker Processes Before Failure Events," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 351-362, January.
    15. Chen, Xuerong & Tang, Niansheng & Zhou, Yong, 2016. "Quantile regression of longitudinal data with informative observation times," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 176-188.
    16. Dongxiao Han & Xiaogang Su & Liuquan Sun & Zhou Zhang & Lei Liu, 2020. "Variable selection in joint frailty models of recurrent and terminal events," Biometrics, The International Biometric Society, vol. 76(4), pages 1330-1339, December.
    17. Gongjun Xu & Sy Han Chiou & Chiung-Yu Huang & Mei-Cheng Wang & Jun Yan, 2017. "Joint Scale-Change Models for Recurrent Events and Failure Time," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 794-805, April.
    18. Russell T. Shinohara & Yifei Sun & Mei-Cheng Wang, 2018. "Alternating event processes during lifetimes: population dynamics and statistical inference," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 110-125, January.
    19. Zhao, Qiang & Sun, Jianguo, 2006. "Semiparametric and nonparametric analysis of recurrent events with observation gaps," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1924-1933, December.
    20. He, Haijin & Pan, Deng & Sun, Liuquan & Li, Yimei & Robison, Leslie L. & Song, Xinyuan, 2017. "Analysis of a fixed center effect additive rates model for recurrent event data," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 186-197.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:68:y:2012:i:2:p:637-647. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.