IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v64y2008i4p1090-1099.html
   My bibliography  Save this article

Regression Survival Analysis with an Assumed Copula for Dependent Censoring: A Sensitivity Analysis Approach

Author

Listed:
  • Xuelin Huang
  • Nan Zhang

Abstract

No abstract is available for this item.

Suggested Citation

  • Xuelin Huang & Nan Zhang, 2008. "Regression Survival Analysis with an Assumed Copula for Dependent Censoring: A Sensitivity Analysis Approach," Biometrics, The International Biometric Society, vol. 64(4), pages 1090-1099, December.
    • Handle: RePEc:bla:biomet:v:64:y:2008:i:4:p:1090-1099
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2008.00986.x
    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. Daniel O. Scharfstein, 2002. "Estimation of the failure time distribution in the presence of informative censoring," Biometrika, Biometrika Trust, vol. 89(3), pages 617-634, August.
    2. Xuelin Huang & Robert A. Wolfe, 2002. "A Frailty Model for Informative Censoring," Biometrics, The International Biometric Society, vol. 58(3), pages 510-520, September.
    3. Daniel Scharfstein & James M. Robins & Wesley Eddings & Andrea Rotnitzky, 2001. "Inference in Randomized Studies with Informative Censoring and Discrete Time-to-Event Endpoints," Biometrics, The International Biometric Society, vol. 57(2), pages 404-413, June.
    4. Jiameng Zhang & Daniel F. Heitjan, 2006. "A Simple Local Sensitivity Analysis Tool for Nonignorable Coarsening: Application to Dependent Censoring," Biometrics, The International Biometric Society, vol. 62(4), pages 1260-1268, December.
    5. Fotios Siannis, 2004. "Applications of a Parametric Model for Informative Censoring," Biometrics, The International Biometric Society, vol. 60(3), pages 704-714, September.
    6. Limin Peng & Jason P. Fine, 2007. "Regression Modeling of Semicompeting Risks Data," Biometrics, The International Biometric Society, vol. 63(1), pages 96-108, March.
    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. Yi‐Hau Chen, 2010. "Semiparametric marginal regression analysis for dependent competing risks under an assumed copula," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 235-251, March.
    2. Chen, Xuerong & Hu, Tao & Sun, Jianguo, 2017. "Sieve maximum likelihood estimation for the proportional hazards model under informative censoring," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 224-234.
    3. Paramahansa Pramanik, 2024. "Dependence on Tail Copula," J, MDPI, vol. 7(2), pages 1-26, April.
    4. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini, 2018. "Bayesian non‐parametric conditional copula estimation of twin data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 523-548, April.
    5. Cuihong Zhang & Jing Ning & Steven H. Belle & Robert H. Squires & Jianwen Cai & Ruosha Li, 2022. "Assessing predictive discrimination performance of biomarkers in the presence of treatment‐induced dependent censoring," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1137-1157, November.
    6. Kim, Dongwoo, 2023. "Partially identifying competing risks models: An application to the war on cancer," Journal of Econometrics, Elsevier, vol. 234(2), pages 536-564.
    7. An-Min Tang & Nian-Sheng Tang & Dalei Yu, 2023. "Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(4), pages 888-918, October.
    8. Deresa, N.W. & Van Keilegom, I. & Antonio, K., 2022. "Copula-based inference for bivariate survival data with left truncation and dependent censoring," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 1-21.
    9. Woraphon Yamaka & Paravee Maneejuk & Rungrapee Phadkantha & Wiranya Puntoon & Payap Tarkhamtham & Tatcha Sudtasan, 2023. "Survival and Duration Analysis of MSMEs in Chiang Mai, Thailand: Evidence from the Post-COVID-19 Recovery," Mathematics, MDPI, vol. 11(4), pages 1-21, February.
    10. Deresa, Negera Wakgari & Van Keilegom, Ingrid, 2020. "A multivariate normal regression model for survival data subject to different types of dependent censoring," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    11. Chia-Hui Huang, 2019. "Mixture regression models for the gap time distributions and illness–death processes," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 168-188, January.
    12. Sangbum Choi & Xuelin Huang, 2014. "Maximum likelihood estimation of semiparametric mixture component models for competing risks data," Biometrics, The International Biometric Society, vol. 70(3), pages 588-598, September.
    13. Lo, Simon M.S. & Wilke, Ralf A. & Emura, Takeshi, 2024. "A semiparametric model for the cause-specific hazard under risk proportionality," Computational Statistics & Data Analysis, Elsevier, vol. 195(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. Sedigheh Mirzaei Salehabadi & Debasis Sengupta & Rituparna Das, 2015. "Parametric Estimation of Menarcheal Age Distribution Based on Recall Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 290-305, March.
    2. Miran A. Jaffa & Ayad A. Jaffa, 2019. "A Likelihood-Based Approach with Shared Latent Random Parameters for the Longitudinal Binary and Informative Censoring Processes," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 597-613, December.
    3. Ungolo, Francesco & van den Heuvel, Edwin R., 2024. "A Dirichlet process mixture regression model for the analysis of competing risk events," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 95-113.
    4. Lu, Zudi & Zhang, Wenyang, 2012. "Semiparametric likelihood estimation in survival models with informative censoring," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 187-211.
    5. Qui Tran & Kelley M. Kidwell & Alex Tsodikov, 2018. "A joint model of cancer incidence, metastasis, and mortality," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(3), pages 385-406, July.
    6. Richard J. Cook & Jerald F. Lawless, 2020. "Failure time studies with intermittent observation and losses to follow‐up," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1035-1063, December.
    7. 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.
    8. Heng Chen & Daniel F. Heitjan, 2022. "Analysis of local sensitivity to nonignorability with missing outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(4), pages 1342-1352, December.
    9. Annalisa Orenti & Patrizia Boracchi & Giuseppe Marano & Elia Biganzoli & Federico Ambrogi, 2022. "A pseudo-values regression model for non-fatal event free survival in the presence of semi-competing risks," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 709-727, September.
    10. Lei Liu & Xuelin Huang & John O'Quigley, 2008. "Analysis of Longitudinal Data in the Presence of Informative Observational Times and a Dependent Terminal Event, with Application to Medical Cost Data," Biometrics, The International Biometric Society, vol. 64(3), pages 950-958, September.
    11. Greg DiRienzo, 2004. "Nonparametric Comparison of Two Survival-Time Distributions in the Presence of Dependent Censoring," Harvard University Biostatistics Working Paper Series 1000, Berkeley Electronic Press.
    12. Samaneh Mahabadi & Mojtaba Ganjali, 2015. "A Bayesian approach for sensitivity analysis of incomplete multivariate longitudinal data with potential nonrandom dropout," METRON, Springer;Sapienza Università di Roma, vol. 73(3), pages 397-417, December.
    13. Fei Jiang & Sebastien Haneuse, 2017. "A Semi-parametric Transformation Frailty Model for Semi-competing Risks Survival Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 112-129, March.
    14. A. G. DiRienzo, 2003. "Nonparametric Comparison of Two Survival-Time Distributions in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 59(3), pages 497-504, September.
    15. Jie Zhu & Blanca Gallego, 2021. "Continuous Treatment Recommendation with Deep Survival Dose Response Function," Papers 2108.10453, arXiv.org, revised Sep 2023.
    16. Yang Li & Hao Liu & Xiaoshen Wang & Wanzhu Tu, 2022. "Semi‐parametric time‐to‐event modelling of lengths of hospital stays," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1623-1647, November.
    17. Fotios Siannis, 2004. "Applications of a Parametric Model for Informative Censoring," Biometrics, The International Biometric Society, vol. 60(3), pages 704-714, September.
    18. Su, Pei-Fang & Chi, Yunchan & Li, Chung-I & Shyr, Yu & Liao, Yi-De, 2011. "Analyzing survival curves at a fixed point in time for paired and clustered right-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1617-1628, April.
    19. Dongxiao Han & Xiaogang Su & Liuquan Sun & Zhou Zhang & Lei Liu, 2020. "Variable selection in joint frailty models of recurrent and terminal events," Biometrics, The International Biometric Society, vol. 76(4), pages 1330-1339, December.
    20. Chenguang Wang & Michael J. Daniels, 2011. "A Note on MAR, Identifying Restrictions, Model Comparison, and Sensitivity Analysis in Pattern Mixture Models with and without Covariates for Incomplete Data," Biometrics, The International Biometric Society, vol. 67(3), pages 810-818, 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:bla:biomet:v:64:y:2008:i:4:p:1090-1099. 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.