IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v62y2006i4p1037-1043.html
   My bibliography  Save this article

Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited

Author

Listed:
  • Fushing Hsieh
  • Yi-Kuan Tseng
  • Jane-Ling Wang

Abstract

No abstract is available for this item.

Suggested Citation

  • Fushing Hsieh & Yi-Kuan Tseng & Jane-Ling Wang, 2006. "Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited," Biometrics, The International Biometric Society, vol. 62(4), pages 1037-1043, December.
  • Handle: RePEc:bla:biomet:v:62:y:2006:i:4:p:1037-1043
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2006.00570.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. Xiao Song & Marie Davidian & Anastasios A. Tsiatis, 2002. "A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data," Biometrics, The International Biometric Society, vol. 58(4), pages 742-753, December.
    Full references (including those not matched with items on IDEAS)

    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. Rizopoulos, Dimitris, 2012. "Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 491-501.
    2. Paul S. Albert & Joanna H. Shih, 2010. "On Estimating the Relationship between Longitudinal Measurements and Time-to-Event Data Using a Simple Two-Stage Procedure," Biometrics, The International Biometric Society, vol. 66(3), pages 983-987, September.
    3. Melkamu Molla Ferede & Samuel Mwalili & Getachew Dagne & Simon Karanja & Workagegnehu Hailu & Mahmoud El-Morshedy & Afrah Al-Bossly, 2022. "A Semiparametric Bayesian Joint Modelling of Skewed Longitudinal and Competing Risks Failure Time Data: With Application to Chronic Kidney Disease," Mathematics, MDPI, vol. 10(24), pages 1-21, December.
    4. Xianzheng Huang & Leonard A. Stefanski & Marie Davidian, 2009. "Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process," Biometrics, The International Biometric Society, vol. 65(3), pages 719-727, September.
    5. Zhang, Zili & Charalambous, Christiana & Foster, Peter, 2023. "A Gaussian copula joint model for longitudinal and time-to-event data with random effects," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).
    6. Roula Tsonaka & Geert Verbeke & Emmanuel Lesaffre, 2009. "A Semi-Parametric Shared Parameter Model to Handle Nonmonotone Nonignorable Missingness," Biometrics, The International Biometric Society, vol. 65(1), pages 81-87, March.
    7. Qi Gong & Douglas E. Schaubel, 2013. "Partly Conditional Estimation of the Effect of a Time-Dependent Factor in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 69(2), pages 338-347, June.
    8. Elizabeth R. Brown & Joseph G. Ibrahim & Victor DeGruttola, 2005. "A Flexible B-Spline Model for Multiple Longitudinal Biomarkers and Survival," Biometrics, The International Biometric Society, vol. 61(1), pages 64-73, March.
    9. Dimitris Rizopoulos, 2011. "Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data," Biometrics, The International Biometric Society, vol. 67(3), pages 819-829, September.
    10. Jaeun Choi & Jianwen Cai & Donglin Zeng, 2017. "Penalized Likelihood Approach for Simultaneous Analysis of Survival Time and Binary Longitudinal Outcome," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(2), pages 190-216, November.
    11. Yih‐Huei Huang & Wen‐Han Hwang & Fei‐Yin Chen, 2016. "Improving efficiency using the Rao–Blackwell theorem in corrected and conditional score estimation methods for joint models," Biometrics, The International Biometric Society, vol. 72(4), pages 1136-1144, December.
    12. Dimitris Rizopoulos & Geert Verbeke & Emmanuel Lesaffre & Yves Vanrenterghem, 2008. "A Two-Part Joint Model for the Analysis of Survival and Longitudinal Binary Data with Excess Zeros," Biometrics, The International Biometric Society, vol. 64(2), pages 611-619, June.
    13. Robert M. Elashoff & Gang Li & Ning Li, 2008. "A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types," Biometrics, The International Biometric Society, vol. 64(3), pages 762-771, September.
    14. Xiaobing Zhao & Xian Zhou, 2015. "Semiparametric models of longitudinal and time-to-event data with applications to HIV viral dynamics and CD4 counts," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2461-2477, November.
    15. Wang, Wan-Lun & Fan, Tsai-Hung, 2012. "Bayesian analysis of multivariate t linear mixed models using a combination of IBF and Gibbs samplers," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 300-310.
    16. Vock, David & Davidian, Marie & Tsiatis, Anastasios, 2014. "SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(c02).
    17. Y. K. Tseng & Y. R. Su & M. Mao & J. L. Wang, 2015. "An extended hazard model with longitudinal covariates," Biometrika, Biometrika Trust, vol. 102(1), pages 135-150.
    18. Xiao Song & Yijian Huang, 2005. "On Corrected Score Approach for Proportional Hazards Model with Covariate Measurement Error," Biometrics, The International Biometric Society, vol. 61(3), pages 702-714, September.
    19. Dimitris Rizopoulos & Geert Verbeke & Emmanuel Lesaffre, 2009. "Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 637-654, June.
    20. Samuel I. Watson & Richard J. Lilford & Jianxia Sun & Julian Bion, 2021. "Estimating the effect of health service delivery interventions on patient length of stay: A Bayesian survival analysis approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1164-1186, November.

    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:62:y:2006:i:4:p:1037-1043. 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.