IDEAS home Printed from https://ideas.repec.org/a/bpj/ijbist/v8y2012i1n4.html
   My bibliography  Save this article

Estimation of the Mean Frequency Function for Recurrent Events when Ascertainment of Events Is Delayed

Author

Listed:
  • Casper T. Charles

    (University of Utah)

  • Cook Thomas D.

    (University of Wisconsin, Madison)

Abstract

In many large clinical trials there are delays between the time at which events occur and the time at which they are reported. Estimators of the mean frequency function for recurrent events that are currently used are inconsistent in these circumstances. We propose two new estimators to be used when events are reported with delay. One method is a basic inverse probability of censoring weighting approach, while the other explicitly estimates the distribution of the reporting delays. The asymptotic properties of these estimators are discussed and variance estimators are given. We examine the results of simulations comparing the new estimators to each other and to existing estimators that do not properly account for the delays. We also calculate some of these quantities using data from TNT, a clinical trial in which there were delays and events of interest were recurrent.

Suggested Citation

  • Casper T. Charles & Cook Thomas D., 2012. "Estimation of the Mean Frequency Function for Recurrent Events when Ascertainment of Events Is Delayed," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-20, February.
  • Handle: RePEc:bpj:ijbist:v:8:y:2012:i:1:n:4
    DOI: 10.1515/1557-4679.1303
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/1557-4679.1303
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.1515/1557-4679.1303?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Ronald E. Gangnon, 2004. "Sample-size formula for clustered survival data using weighted log-rank statistics," Biometrika, Biometrika Trust, vol. 91(2), pages 263-275, June.
    2. Debashis Ghosh & D. Y. Lin, 2000. "Nonparametric Analysis of Recurrent Events and Death," Biometrics, The International Biometric Society, vol. 56(2), pages 554-562, June.
    Full references (including those not matched with items on IDEAS)

    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. Julie K. Furberg & Per K. Andersen & Sofie Korn & Morten Overgaard & Henrik Ravn, 2023. "Bivariate pseudo-observations for recurrent event analysis with terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 256-287, April.
    2. 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.
    3. Giuliana Cortese & Thomas H. Scheike, 2022. "Efficient estimation of the marginal mean of recurrent events," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1787-1821, November.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Jianghao Li & Sin-Ho Jung, 2022. "Sample size calculation for clustered survival data under subunit randomization," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(1), pages 40-67, January.
    9. Xuelin Huang & Lei Liu, 2007. "A Joint Frailty Model for Survival and Gap Times Between Recurrent Events," Biometrics, The International Biometric Society, vol. 63(2), pages 389-397, June.
    10. Donglin Zeng & D. Y. Lin, 2009. "Semiparametric Transformation Models with Random Effects for Joint Analysis of Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 65(3), pages 746-752, September.
    11. 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.
    12. Xiaodong Luo & Hong Tian & Surya Mohanty & Wei Yann Tsai, 2015. "An alternative approach to confidence interval estimation for the win ratio statistic," Biometrics, The International Biometric Society, vol. 71(1), pages 139-145, March.
    13. Debashis Ghosh & D. Y. Lin, 2003. "Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 59(4), pages 877-885, December.
    14. Yassin Mazroui & Audrey Mauguen & Simone Mathoulin-Pélissier & Gaetan MacGrogan & Véronique Brouste & Virginie Rondeau, 2016. "Time-varying coefficients in a multivariate frailty model: Application to breast cancer recurrences of several types and death," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(2), pages 191-215, April.
    15. Tianyu Zhan & Douglas E. Schaubel, 2019. "Semiparametric temporal process regression of survival-out-of-hospital," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 322-340, April.
    16. A.K.M. Fazlur Rahman & James D. Lynch & Edsel A. Peña, 2014. "Nonparametric Bayes estimation of gap-time distribution with recurrent event data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 575-598, September.
    17. Jun Yan & Yu Cheng & Jason P. Fine & HuiChuan J. Lai, 2010. "Uncovering Symptom Progression History from Disease Registry Data with Application to Young Cystic Fibrosis Patients," Biometrics, The International Biometric Society, vol. 66(2), pages 594-602, June.
    18. 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.
    19. Bingshu E. Chen & Joan L. Kramer & Mark H. Greene & Philip S. Rosenberg, 2008. "Competing Risks Analysis of Correlated Failure Time Data," Biometrics, The International Biometric Society, vol. 64(1), pages 172-179, March.
    20. Lu Mao, 2023. "Nonparametric inference of general while‐alive estimands for recurrent events," Biometrics, The International Biometric Society, vol. 79(3), pages 1749-1760, September.

    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:bpj:ijbist:v:8:y:2012:i:1:n:4. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.