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Analysis of the HIV/AIDS Data Using Joint Modeling of Longitudinal (k,l)-Inflated Count and Time to Event Data in Clinical Trials

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  • Mojtaba Zeinali Najafabadi

    (Shahid Beheshti University)

  • Ehsan Bahrami Samani

    (Shahid Beheshti University)

Abstract

Generalized linear mixed effect models (GLMEMs) are widely applied for the analysis of correlated non-Gaussian data such as those found in longitudinal studies. On the other hand, the Cox (proportional hazards, PHs) and the accelerated failure time (AFT) regression models are two well-known approaches in survival analysis to modeling time to event (TTE) data. In this article, we develop joint modeling of longitudinal count (LC) and TTE data and consider extensions with fixed effects and parametric random effects in our proposed joint models. The LC response is inflated in two points k and l (k

Suggested Citation

  • Mojtaba Zeinali Najafabadi & Ehsan Bahrami Samani, 2025. "Analysis of the HIV/AIDS Data Using Joint Modeling of Longitudinal (k,l)-Inflated Count and Time to Event Data in Clinical Trials," Annals of Data Science, Springer, vol. 12(2), pages 695-719, April.
    • Handle: RePEc:spr:aodasc:v:12:y:2025:i:2:d:10.1007_s40745-024-00532-5
    DOI: 10.1007/s40745-024-00532-5
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    References listed on IDEAS

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    1. 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.
    2. T. Baghfalaki & M. Ganjali & D. Berridge, 2014. "Joint modeling of multivariate longitudinal mixed measurements and time to event data using a Bayesian approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(9), pages 1934-1955, September.
    3. Lang Wu & Wei Liu & Grace Y. Yi & Yangxin Huang, 2012. "Analysis of Longitudinal and Survival Data: Joint Modeling, Inference Methods, and Issues," Journal of Probability and Statistics, Hindawi, vol. 2012, pages 1-17, December.
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