IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v73y2017i3p857-865.html
   My bibliography  Save this article

Semiparametric regression analysis of interval-censored competing risks data

Author

Listed:
  • Lu Mao
  • Dan-Yu Lin
  • Donglin Zeng

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:biomet:v:73:y:2017:i:3:p:857-865
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/biom.12664
    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. Groeneboom,Piet & Jongbloed,Geurt, 2014. "Nonparametric Estimation under Shape Constraints," Cambridge Books, Cambridge University Press, number 9780521864015, October.
    2. Chenxi Li & Jason P. Fine, 2013. "Smoothed nonparametric estimation for current status competing risks data," Biometrika, Biometrika Trust, vol. 100(1), pages 173-187.
    3. Wenbin Lu, 2004. "On semiparametric transformation cure models," Biometrika, Biometrika Trust, vol. 91(2), pages 331-343, June.
    4. Nicholas P. Jewell, 2003. "Nonparametric estimation from current status data with competing risks," Biometrika, Biometrika Trust, vol. 90(1), pages 183-197, March.
    5. Li, Chenxi, 2016. "The Fine–Gray model under interval censored competing risks data," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 327-344.
    6. Donglin Zeng & Lu Mao & D. Y. Lin, 2016. "Maximum likelihood estimation for semiparametric transformation models with interval-censored data," Biometrika, Biometrika Trust, vol. 103(2), pages 253-271.
    7. 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.
    8. 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.
    9. Kani Chen, 2002. "Semiparametric analysis of transformation models with censored data," Biometrika, Biometrika Trust, vol. 89(3), pages 659-668, August.
    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. Fei Gao & Kwun Chuen Gary Chan, 2019. "Semiparametric regression analysis of length‐biased interval‐censored data," Biometrics, The International Biometric Society, vol. 75(1), pages 121-132, March.

    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. "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.
    2. Li, Chenxi, 2016. "The Fine–Gray model under interval censored competing risks data," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 327-344.
    3. 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.
    4. Du, Mingyue & Li, Huiqiong & Sun, Jianguo, 2021. "Regression analysis of censored data with nonignorable missing covariates and application to Alzheimer Disease," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    5. Yanqing Sun & Qingning Zhou & Peter B. Gilbert, 2023. "Analysis of the Cox Model with Longitudinal Covariates with Measurement Errors and Partly Interval Censored Failure Times, with Application to an AIDS Clinical Trial," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(2), pages 430-454, July.
    6. Huang, Bin & Wang, Qihua, 2010. "Semiparametric analysis based on weighted estimating equations for transformation models with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2078-2090, October.
    7. Donglin Zeng & Fei Gao & D. Y. Lin, 2017. "Maximum likelihood estimation for semiparametric regression models with multivariate interval-censored data," Biometrika, Biometrika Trust, vol. 104(3), pages 505-525.
    8. Li, Shuwei & Hu, Tao & Zhao, Xingqiu & Sun, Jianguo, 2019. "A class of semiparametric transformation cure models for interval-censored failure time data," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 153-165.
    9. 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.
    10. Xi Ning & Yinghao Pan & Yanqing Sun & Peter B. Gilbert, 2023. "A semiparametric Cox–Aalen transformation model with censored data," Biometrics, The International Biometric Society, vol. 79(4), pages 3111-3125, December.
    11. Yilong Zhang & Xiaoxia Han & Yongzhao Shao, 2021. "The ROC of Cox proportional hazards cure models with application in cancer studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(2), pages 195-215, April.
    12. Ruiwen Zhou & Huiqiong Li & Jianguo Sun & Niansheng Tang, 2022. "A new approach to estimation of the proportional hazards model based on interval-censored data with missing covariates," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(3), pages 335-355, July.
    13. 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.
    14. Sangbum Choi & Xuelin Huang, 2012. "A General Class of Semiparametric Transformation Frailty Models for Nonproportional Hazards Survival Data," Biometrics, The International Biometric Society, vol. 68(4), pages 1126-1135, December.
    15. 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.
    16. Gu, Minggao & Wu, Yueqin & Huang, Bin, 2014. "Partial marginal likelihood estimation for general transformation models," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 1-18.
    17. Wang, Xuan & Wang, Qihua, 2015. "Semiparametric linear transformation model with differential measurement error and validation sampling," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 67-80.
    18. Huazhen Lin & Ling Zhou & Chunhong Li & Yi Li, 2014. "Semiparametric transformation models for semicompeting survival data," Biometrics, The International Biometric Society, vol. 70(3), pages 599-607, September.
    19. Mao, Lu, 2022. "Identification of the outcome distribution and sensitivity analysis under weak confounder–instrument interaction," Statistics & Probability Letters, Elsevier, vol. 189(C).
    20. Pao-sheng Shen & Yi Liu, 2019. "Pseudo maximum likelihood estimation for the Cox model with doubly truncated data," Statistical Papers, Springer, vol. 60(4), pages 1207-1224, August.

    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:73:y:2017:i:3:p:857-865. 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.