IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v70y2014i1p1-9.html
   My bibliography  Save this article

Parametric likelihood inference for interval censored competing risks data

Author

Listed:
  • Michael G. Hudgens
  • Chenxi Li
  • Jason P. Fine

Abstract

No abstract is available for this item.

Suggested Citation

  • Michael G. Hudgens & Chenxi Li & Jason P. Fine, 2014. "Parametric likelihood inference for interval censored competing risks data," Biometrics, The International Biometric Society, vol. 70(1), pages 1-9, March.
  • Handle: RePEc:bla:biomet:v:70:y:2014:i:1:p:1-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/biom.12109
    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. Nicholas P. Jewell, 2003. "Nonparametric estimation from current status data with competing risks," Biometrika, Biometrika Trust, vol. 90(1), pages 183-197, March.
    2. Anton Schick & Qiqing Yu, 2000. "Consistency of the GMLE with Mixed Case Interval‐Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(1), pages 45-55, March.
    3. Michael G. Hudgens & Glen A. Satten & Ira M. Longini, 2001. "Nonparametric Maximum Likelihood Estimation for Competing Risks Survival Data Subject to Interval Censoring and Truncation," Biometrics, The International Biometric Society, vol. 57(1), pages 74-80, March.
    4. Jong‐Hyeon Jeong & Jason Fine, 2006. "Direct parametric inference for the cumulative incidence function," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 187-200, April.
    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. Margarita Moreno-Betancur & Grégoire Rey & Aurélien Latouche, 2015. "Direct likelihood inference and sensitivity analysis for competing risks regression with missing causes of failure," Biometrics, The International Biometric Society, vol. 71(2), pages 498-507, June.
    2. Lu Mao & Dan-Yu Lin & Donglin Zeng, 2017. "Semiparametric regression analysis of interval-censored competing risks data," Biometrics, The International Biometric Society, vol. 73(3), pages 857-865, September.
    3. Ryan Sun & Liang Zhu & Yimei Li & Yutaka Yasui & Leslie Robison, 2023. "Inference for set‐based effects in genetic association studies with interval‐censored outcomes," Biometrics, The International Biometric Society, vol. 79(2), pages 1573-1585, June.
    4. Yosra Yousif & Faiz Elfaki & Meftah Hrairi & Oyelola Adegboye, 2022. "Bayesian Analysis of Masked Competing Risks Data Based on Proportional Subdistribution Hazards Model," Mathematics, MDPI, vol. 10(17), pages 1-10, August.
    5. Li, Chenxi, 2016. "Cause-specific hazard regression for competing risks data under interval censoring and left truncation," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 197-208.
    6. Li, Chenxi, 2016. "The Fine–Gray model under interval censored competing risks data," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 327-344.

    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. Li, Chenxi, 2016. "The Fine–Gray model under interval censored competing risks data," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 327-344.
    2. Li, Chenxi, 2016. "Cause-specific hazard regression for competing risks data under interval censoring and left truncation," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 197-208.
    3. Lu Mao & Dan-Yu Lin & Donglin Zeng, 2017. "Semiparametric regression analysis of interval-censored competing risks data," Biometrics, The International Biometric Society, vol. 73(3), pages 857-865, September.
    4. Tamalika Koley & Anup Dewanji, 2019. "Revisiting Non-Parametric Maximum Likelihood Estimation of Current Status Data with Competing Risks," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 39-59, June.
    5. Lu Mao & D. Y. Lin, 2017. "Efficient estimation of semiparametric transformation models for the cumulative incidence of competing risks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 573-587, March.
    6. Michael G. Hudgens & Marloes H. Maathuis & Peter B. Gilbert, 2007. "Nonparametric Estimation of the Joint Distribution of a Survival Time Subject to Interval Censoring and a Continuous Mark Variable," Biometrics, The International Biometric Society, vol. 63(2), pages 372-380, June.
    7. Somnath Datta & Rajeshwari Sundaram, 2006. "Nonparametric Estimation of Stage Occupation Probabilities in a Multistage Model with Current Status Data," Biometrics, The International Biometric Society, vol. 62(3), pages 829-837, September.
    8. Pao-sheng Shen, 2022. "Nonparametric estimation for competing risks survival data subject to left truncation and interval censoring," Computational Statistics, Springer, vol. 37(1), pages 29-42, March.
    9. Peijie Wang & Hui Zhao & Jianguo Sun, 2016. "Regression analysis of case K interval‐censored failure time data in the presence of informative censoring," Biometrics, The International Biometric Society, vol. 72(4), pages 1103-1112, December.
    10. Qiqing Yu & George Wong & Linxiong Li, 2001. "Asymptotic Properties of Self-Consistent Estimators with Mixed Interval-Censored Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(3), pages 469-486, September.
    11. Yosra Yousif & Faiz Elfaki & Meftah Hrairi & Oyelola Adegboye, 2022. "Bayesian Analysis of Masked Competing Risks Data Based on Proportional Subdistribution Hazards Model," Mathematics, MDPI, vol. 10(17), pages 1-10, August.
    12. Serge M. A. Somda & Eve Leconte & Andrew Kramar & Nicolas Penel & Christine Chevreau & Martine Delannes & Maria Rios & Thomas Filleron, 2014. "Determining the Length of Posttherapeutic Follow-up for Cancer Patients Using Competing Risks Modeling," Medical Decision Making, , vol. 34(2), pages 168-179, February.
    13. Halina Frydman & Michael Szarek, 2009. "Nonparametric Estimation in a Markov “Illness–Death” Process from Interval Censored Observations with Missing Intermediate Transition Status," Biometrics, The International Biometric Society, vol. 65(1), pages 143-151, March.
    14. S. R. Haile & J.-H. Jeong & X. Chen & Y. Cheng, 2016. "A 3-parameter Gompertz distribution for survival data with competing risks, with an application to breast cancer data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(12), pages 2239-2253, September.
    15. Marra, Giampiero & Farcomeni, Alessio & Radice, Rosalba, 2021. "Link-based survival additive models under mixed censoring to assess risks of hospital-acquired infections," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    16. Lim, Johan & Wang, Xinlei & Choi, Wanseok, 2009. "Maximum likelihood estimation of ordered multinomial probabilities by geometric programming," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 889-893, February.
    17. Wang, Yong, 2008. "Dimension-reduced nonparametric maximum likelihood computation for interval-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2388-2402, January.
    18. Gürler, Ülkü & Deniz Yenigün, C., 2011. "Full and conditional likelihood approaches for hazard change-point estimation with truncated and censored data," Computational Statistics & Data Analysis, Elsevier, vol. 55(10), pages 2856-2870, October.
    19. Jiahui Li & Qiqing Yu, 2016. "A consistent NPMLE of the joint distribution function with competing risks data under the dependent masking and right-censoring model," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(1), pages 63-99, January.
    20. Yuet-Yee Wong, Linda & Yu, Qiqing, 2007. "A bivariate interval censorship model for partnership formation," Journal of Multivariate Analysis, Elsevier, vol. 98(2), pages 370-383, February.

    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:70:y:2014:i:1:p:1-9. 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.