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Latent Class Models for Joint Analysis of Longitudinal Biomarker and Event Process Data: Application to Longitudinal Prostate-Specific Antigen Readings and Prostate Cancer

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  • Lin H.
  • Turnbull B. W.
  • McCulloch C. E.
  • Slate E. H.

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Suggested Citation

  • Lin H. & Turnbull B. W. & McCulloch C. E. & Slate E. H., 2002. "Latent Class Models for Joint Analysis of Longitudinal Biomarker and Event Process Data: Application to Longitudinal Prostate-Specific Antigen Readings and Prostate Cancer," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 53-65, March.
    • Handle: RePEc:bes:jnlasa:v:97:y:2002:m:march:p:53-65
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    Cited by:

    1. Cheng Zheng & Lei Liu, 2022. "Quantifying direct and indirect effect for longitudinal mediator and survival outcome using joint modeling approach," Biometrics, The International Biometric Society, vol. 78(3), pages 1233-1243, September.
    2. Jiehuan Sun & Jose D. Herazo‐Maya & Philip L. Molyneaux & Toby M. Maher & Naftali Kaminski & Hongyu Zhao, 2019. "Regularized Latent Class Model for Joint Analysis of High‐Dimensional Longitudinal Biomarkers and a Time‐to‐Event Outcome," Biometrics, The International Biometric Society, vol. 75(1), pages 69-77, March.
    3. 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.
    4. Bartolucci, Al & Bae, Sejong & Singh, Karan & Griffith, H. Randall, 2009. "An examination of Bayesian statistical approaches to modeling change in cognitive decline in an Alzheimer's disease population," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(3), pages 561-571.
    5. Proust-Lima, Cécile & Philipps, Viviane & Liquet, Benoit, 2017. "Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i02).
    6. Jaeun Choi & Donglin Zeng & Andrew F. Olshan & Jianwen Cai, 2018. "Joint modeling of survival time and longitudinal outcomes with flexible random effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 126-152, January.
    7. Proust-Lima, Cécile & Joly, Pierre & Dartigues, Jean-François & Jacqmin-Gadda, Hélène, 2009. "Joint modelling of multivariate longitudinal outcomes and a time-to-event: A nonlinear latent class approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1142-1154, February.
    8. Beom Seuk Hwang & Zhen Chen & Germaine M. Buck Louis & Paul S. Albert, 2019. "A Bayesian multi‐dimensional couple‐based latent risk model with an application to infertility," Biometrics, The International Biometric Society, vol. 75(1), pages 315-325, March.
    9. Xiaoyu Che & John Angus, 2016. "A new joint model of recurrent event data with the additive hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(7), pages 763-787, October.
    10. Han, Jun, 2009. "Initial classification of joint data in EM estimation of latent class joint model," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2313-2323, November.
    11. 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).

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