IDEAS home Printed from https://ideas.repec.org/a/spr/lifeda/v26y2020i2d10.1007_s10985-019-09477-x.html
   My bibliography  Save this article

Semiparametric regression analysis of doubly censored failure time data from cohort studies

Author

Listed:
  • Shuwei Li

    (Guangzhou University)

  • Jianguo Sun

    (University of Missouri)

  • Tian Tian

    (University of Missouri)

  • Xia Cui

    (Guangzhou University)

Abstract

Doubly censored failure time data occur when the failure time of interest represents the elapsed time between two events, an initial event and a subsequent event, and the observations on both events may suffer censoring. A well-known example of such data is given by the acquired immune deficiency syndrome (AIDS) cohort study in which the two events are HIV infection and AIDS diagnosis, and several inference methods have been developed in the literature for their regression analysis. However, all of them only apply to limited situations or focus on a single model. In this paper, we propose a marginal likelihood approach based on a general class of semiparametric transformation models, which can be applied to much more general situations. For the implementation, we develop a two-step procedure that makes use of both the multiple imputation technique and a novel EM algorithm. The asymptotic properties of the resulting estimators are established by using the modern empirical process theory, and the simulation study conducted suggests that the method works well in practical situations. An application is also provided.

Suggested Citation

  • Shuwei Li & Jianguo Sun & Tian Tian & Xia Cui, 2020. "Semiparametric regression analysis of doubly censored failure time data from cohort studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 315-338, April.
  • Handle: RePEc:spr:lifeda:v:26:y:2020:i:2:d:10.1007_s10985-019-09477-x
    DOI: 10.1007/s10985-019-09477-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10985-019-09477-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10985-019-09477-x?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. Wen, Chi-Chung & Chen, Yi-Hau, 2011. "Nonparametric maximum likelihood analysis of clustered current status data with the gamma-frailty Cox model," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1053-1060, February.
    2. 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.
    3. Jianguo Sun & Qiming Liao & Marcello Pagano, 1999. "Regression Analysis of Doubly Censored Failure Time Data with Applications to AIDS Studies," Biometrics, The International Biometric Society, vol. 55(3), pages 909-914, September.
    4. Yang-Jin Kim, 2006. "Regression Analysis of Doubly Censored Failure Time Data with Frailty," Biometrics, The International Biometric Society, vol. 62(2), pages 458-464, June.
    5. Liuquan Sun & Yang-jin Kim & Jianguo Sun, 2004. "Regression Analysis of Doubly Censored Failure Time Data Using the Additive Hazards Model," Biometrics, The International Biometric Society, vol. 60(3), pages 637-643, September.
    6. Zhiguo Li & Kouros Owzar, 2016. "Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 476-486, June.
    7. Donglin Zeng & D. Y. Lin, 2006. "Efficient estimation of semiparametric transformation models for counting processes," Biometrika, Biometrika Trust, vol. 93(3), pages 627-640, September.
    8. T. Cai, 2004. "Semiparametric regression analysis for doubly censored data," Biometrika, Biometrika Trust, vol. 91(2), pages 277-290, June.
    9. 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.
    10. Lianming Wang & Christopher S. McMahan & Michael G. Hudgens & Zaina P. Qureshi, 2016. "A flexible, computationally efficient method for fitting the proportional hazards model to interval-censored data," Biometrics, The International Biometric Society, vol. 72(1), pages 222-231, March.
    11. Wei Pan, 2001. "A Multiple Imputation Approach to Regression Analysis for Doubly Censored Data with Application to AIDS Studies," Biometrics, The International Biometric Society, vol. 57(4), pages 1245-1250, December.
    12. Shuwei Li & Tao Hu & Peijie Wang & Jianguo Sun, 2018. "A Class of Semiparametric Transformation Models for Doubly Censored Failure Time Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 45(3), pages 682-698, September.
    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. Kin Yau Wong & Qingning Zhou & Tao Hu, 2023. "Semiparametric regression analysis of doubly-censored data with applications to incubation period estimation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 87-114, January.
    2. Kang, Kai & Song, Xinyuan, 2022. "Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables," Journal of Multivariate Analysis, Elsevier, vol. 187(C).

    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, 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.
    2. Yu, Binbing, 2010. "A Bayesian MCMC approach to survival analysis with doubly-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1921-1929, August.
    3. Kin Yau Wong & Qingning Zhou & Tao Hu, 2023. "Semiparametric regression analysis of doubly-censored data with applications to incubation period estimation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 87-114, January.
    4. Choi, Taehwa & Kim, Arlene K.H. & Choi, Sangbum, 2021. "Semiparametric least-squares regression with doubly-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
    5. Zhiguo Li & Kouros Owzar, 2016. "Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 476-486, June.
    6. Peijie Wang & Xingwei Tong & Jianguo Sun, 2018. "A semiparametric regression cure model for doubly censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(3), pages 492-508, July.
    7. 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).
    8. Yang-Jin Kim, 2006. "Regression Analysis of Doubly Censored Failure Time Data with Frailty," Biometrics, The International Biometric Society, vol. 62(2), pages 458-464, June.
    9. Chien-Lin Su & Russell J. Steele & Ian Shrier, 2021. "The semiparametric accelerated trend-renewal process for recurrent event data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(3), pages 357-387, July.
    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. Fan Feng & Guanghui Cheng & Jianguo Sun, 2023. "Variable Selection for Length-Biased and Interval-Censored Failure Time Data," Mathematics, MDPI, vol. 11(22), pages 1-20, November.
    12. 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.
    13. Liu, Wenting & Li, Huiqiong & Tang, Niansheng & Lyu, Jun, 2024. "Variational Bayesian approach for analyzing interval-censored data under the proportional hazards model," Computational Statistics & Data Analysis, Elsevier, vol. 195(C).
    14. Liuquan Sun & Yang-jin Kim & Jianguo Sun, 2004. "Regression Analysis of Doubly Censored Failure Time Data Using the Additive Hazards Model," Biometrics, The International Biometric Society, vol. 60(3), pages 637-643, September.
    15. Qingning Zhou & Jianwen Cai & Haibo Zhou, 2018. "Outcome†dependent sampling with interval†censored failure time data," Biometrics, The International Biometric Society, vol. 74(1), pages 58-67, March.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. Gamage, Prabhashi W. Withana & McMahan, Christopher S. & Wang, Lianming & Tu, Wanzhu, 2018. "A Gamma-frailty proportional hazards model for bivariate interval-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 354-366.

    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:spr:lifeda:v:26:y:2020:i:2:d:10.1007_s10985-019-09477-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.