IDEAS home Printed from https://ideas.repec.org/a/bla/scjsta/v43y2016i2p476-486.html

Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood

Author

Listed:
  • Zhiguo Li
  • Kouros Owzar

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:scjsta:v:43:y:2016:i:2:p:476-486
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/sjos.12186
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Tianxi Cai & Rebecca A. Betensky, 2003. "Hazard Regression for Interval-Censored Data with Penalized Spline," Biometrics, The International Biometric Society, vol. 59(3), pages 570-579, September.
    2. Lan Xue & Hua Liang, 2010. "Polynomial Spline Estimation for a Generalized Additive Coefficient Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 26-46, March.
    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. Minggen Lu, 2015. "Spline estimation of generalised monotonic regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(1), pages 19-39, March.
    5. Minggen Lu & Dana Loomis, 2013. "Spline-based semiparametric estimation of partially linear Poisson regression with single-index models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(4), pages 905-922, December.
    6. Yu, Qiqing & Schick, Anton & Li, Linxiong & Wong, George Y. C., 1998. "Asymptotic properties of the GMLE with case 2 interval-censored data," Statistics & Probability Letters, Elsevier, vol. 37(3), pages 223-228, March.
    7. 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.
    8. Els Goetghebeur & Louise Ryan, 2000. "Semiparametric Regression Analysis of Interval-Censored Data," Biometrics, The International Biometric Society, vol. 56(4), pages 1139-1144, December.
    9. Xue H. & Lam K.F. & Li G., 2004. "Sieve Maximum Likelihood Estimator for Semiparametric Regression Models With Current Status Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 346-356, January.
    10. Torben Martinussen, 2002. "Efficient estimation in additive hazards regression with current status data," Biometrika, Biometrika Trust, vol. 89(3), pages 649-658, August.
    11. Minggen Lu & Ying Zhang & Jian Huang, 2007. "Estimation of the mean function with panel count data using monotone polynomial splines," Biometrika, Biometrika Trust, vol. 94(3), pages 705-718.
    12. 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.
    13. Ying Zhang & Lei Hua & Jian Huang, 2010. "A Spline‐Based Semiparametric Maximum Likelihood Estimation Method for the Cox Model with Interval‐Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 338-354, June.
    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. Mingyue Du & Xiyuan Gao & Ling Chen, 2024. "Regression analysis of doubly censored failure time data with ancillary information," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(3), pages 667-679, July.
    3. 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.

    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. Minggen Lu, 2015. "Spline estimation of generalised monotonic regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(1), pages 19-39, March.
    2. Prabhashi W. Withana Gamage & Monica Chaudari & Christopher S. McMahan & Edwin H. Kim & Michael R. Kosorok, 2020. "An extended proportional hazards model for interval-censored data subject to instantaneous failures," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 158-182, January.
    3. 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.
    4. 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.
    5. Shanshan Lu & Jingjing Wu & Xuewen Lu, 2019. "Efficient estimation of the varying-coefficient partially linear proportional odds model with current status data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(2), pages 173-194, March.
    6. Mingyue Du & Xiyuan Gao & Ling Chen, 2024. "Regression analysis of doubly censored failure time data with ancillary information," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(3), pages 667-679, July.
    7. Xiaoguang Wang & Ziwen Wang, 2021. "EM algorithm for the additive risk mixture cure model with interval-censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(1), pages 91-130, January.
    8. Minggen Lu, 2018. "Spline-based quasi-likelihood estimation of mixed Poisson regression with single-index models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(1), pages 1-17, January.
    9. Baihua He & Yanyan Liu & Yuanshan Wu & Xingqiu Zhao, 2020. "Semiparametric efficient estimation for additive hazards regression with case II interval-censored survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 708-730, October.
    10. Minggen Lu, 2017. "Efficient estimation of quasi-likelihood models using B-splines," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(5), pages 1099-1127, October.
    11. Minggen Lu & Dana Loomis, 2013. "Spline-based semiparametric estimation of partially linear Poisson regression with single-index models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(4), pages 905-922, December.
    12. Ma, Ling & Hu, Tao & Sun, Jianguo, 2016. "Cox regression analysis of dependent interval-censored failure time data," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 79-90.
    13. 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.
    14. Eddie Anderson & Artem Prokhorov & Yajing Zhu, 2020. "A Simple Estimator of Two‐Dimensional Copulas, with Applications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1375-1412, December.
    15. Li, Shuwei & Hu, Tao & Wang, Peijie & Sun, Jianguo, 2017. "Regression analysis of current status data in the presence of dependent censoring with applications to tumorigenicity experiments," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 75-86.
    16. Pao-sheng Shen, 2013. "Regression analysis of interval censored and doubly truncated data with linear transformation models," Computational Statistics, Springer, vol. 28(2), pages 581-596, April.
    17. Shuangge Ma, 2011. "Additive risk model for current status data with a cured subgroup," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(1), pages 117-134, February.
    18. Ying Zhang & Lei Hua & Jian Huang, 2010. "A Spline‐Based Semiparametric Maximum Likelihood Estimation Method for the Cox Model with Interval‐Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 338-354, June.
    19. Ce Zhang & Haiwu Huang & Dipankar Bandyopadhyay & Riyadh Rustam Al-Mosawi & Xuewen Lu, 2025. "Sieve Estimation of the Additive Hazards Model with Bivariate Current Status Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 17(2), pages 251-296, July.
    20. Graciela Boente & Daniela Rodriguez & Pablo Vena, 2020. "Robust estimators in a generalized partly linear regression model under monotony constraints," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 50-89, March.

    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:scjsta:v:43:y:2016:i:2:p:476-486. 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=0303-6898 .

    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.