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Separate and Joint Modeling of Longitudinal and Event Time Data Using Standard Computer Packages

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  • Guo X.
  • Carlin B.P.

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Suggested Citation

  • Guo X. & Carlin B.P., 2004. "Separate and Joint Modeling of Longitudinal and Event Time Data Using Standard Computer Packages," The American Statistician, American Statistical Association, vol. 58, pages 16-24, February.
    • Handle: RePEc:bes:amstat:v:58:y:2004:m:february:p:16-24
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    Citations

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    Cited by:

    1. Janet Niekerk & Haakon Bakka & Håvard Rue, 2023. "Stable Non-Linear Generalized Bayesian Joint Models for Survival-Longitudinal Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 102-128, February.
    2. Chin-Tsang Chiang, 2011. "A more flexible joint latent model for longitudinal and survival time data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(2), pages 151-170, March.
    3. Feng Gao & J. Miller & Chengjie Xiong & Julia Beiser & Mae Gordon, 2011. "A joint-modeling approach to assess the impact of biomarker variability on the risk of developing clinical outcome," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(1), pages 83-100, March.
    4. Dilip C. Nath & Atanu Bhattacharjee, 2014. "Joint longitudinal and survival data modelling: an application in anti-diabetes drug therapeutic effect," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(3), pages 437-452, June.
    5. Liu, Yue & Liu, Lei & Zhou, Jianhui, 2015. "Joint latent class model of survival and longitudinal data: An application to CPCRA study," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 40-50.
    6. Ram Thapa & Harold E. Burkhart & Jie Li & Yili Hong, 2016. "Modeling Clustered Survival Times of Loblolly Pine with Time-dependent Covariates and Shared Frailties," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(1), pages 92-110, March.
    7. Schweitzer, Maurice E. & Hershey, John C. & Bradlow, Eric T., 2006. "Promises and lies: Restoring violated trust," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(1), pages 1-19, September.
    8. Michael J. Crowther & Keith R. Abrams & Paul C. Lambert, 2013. "Joint modeling of longitudinal and survival data," Stata Journal, StataCorp LP, vol. 13(1), pages 165-184, March.
    9. Toshihiro Misumi, 2022. "Joint modeling for longitudinal covariate and binary outcome via h-likelihood," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1225-1243, December.
    10. repec:jss:jstsof:35:i09 is not listed on IDEAS
    11. Rong Fu & Peter B. Gilbert, 2017. "Joint modeling of longitudinal and survival data with the Cox model and two-phase sampling," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 136-159, January.
    12. Wei Yang & Dawei Xie & Qiang Pan & Harold I. Feldman & Wensheng Guo, 2017. "Joint Modeling of Repeated Measures and Competing Failure Events in a Study of Chronic Kidney Disease," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 504-524, December.
    13. Rizopoulos, Dimitris, 2016. "The R Package JMbayes for Fitting Joint Models for Longitudinal and Time-to-Event Data Using MCMC," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(i07).
    14. Martins, Thiago G. & Simpson, Daniel & Lindgren, Finn & Rue, Håvard, 2013. "Bayesian computing with INLA: New features," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 68-83.
    15. Shahedul A. Khan & Nyla Basharat, 2022. "Accelerated failure time models for recurrent event data analysis and joint modeling," Computational Statistics, Springer, vol. 37(4), pages 1569-1597, September.
    16. Liya Fu & Zhuoran Yang & Yan Zhou & You-Gan Wang, 2021. "An efficient Gehan-type estimation for the accelerated failure time model with clustered and censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(4), pages 679-709, October.
    17. Rui Martins, 2022. "A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 41-61, March.
    18. De la Cruz, Rolando & Meza, Cristian & Arribas-Gil, Ana & Carroll, Raymond J., 2016. "Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 94-106.
    19. Walter Dempsey & Peter McCullagh, 2018. "Survival models and health sequences," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(4), pages 550-584, October.
    20. Tyler H. Matta & James Soland, 2019. "Predicting Time to Reclassification for English Learners: A Joint Modeling Approach," Journal of Educational and Behavioral Statistics, , vol. 44(1), pages 78-102, February.
    21. 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).
    22. Horrocks, Julie & Rueffer, Matthew, 2014. "A Bayesian approach to estimating animal density from binary acoustic transects," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 17-25.

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