Ariyo, Oludare and Olobatuyi, Kehinde and Baghfalaki, Taban (2025) A Bayesian Joint Bent-cable Model for Longitudinal Measurements and Survival Time with Heterogeneous Random-effects Distributions. Journal of Biopharmaceutical Statistics. DOI https://doi.org/10.1080/10543406.2025.2450321
Ariyo, Oludare and Olobatuyi, Kehinde and Baghfalaki, Taban (2025) A Bayesian Joint Bent-cable Model for Longitudinal Measurements and Survival Time with Heterogeneous Random-effects Distributions. Journal of Biopharmaceutical Statistics. DOI https://doi.org/10.1080/10543406.2025.2450321
Ariyo, Oludare and Olobatuyi, Kehinde and Baghfalaki, Taban (2025) A Bayesian Joint Bent-cable Model for Longitudinal Measurements and Survival Time with Heterogeneous Random-effects Distributions. Journal of Biopharmaceutical Statistics. DOI https://doi.org/10.1080/10543406.2025.2450321
Abstract
Biomarkers are measured repeatedly in clinical studies until a pre-defined endpoint, such as death from certain causes, is reached. Such repeated measurements may present a dynamic process for understanding when to expect the study's endpoint. Joint modelling is often employed to handle such a model. Typically, shared random effects are assumed to be common to both the longitudinal component and the study's endpoint. These shared random effects usually assume homogeneous and follow a normal distribution. However, identifying homogeneous subgroups is important when the underlying population is heterogeneous. This issue has received little attention in the literature, particularly for multi-phase longitudinal responses. In this paper, we propose a joint modelling approach for longitudinal and survival models using a bent-cable mixed model for longitudinal measurements and a Weibull distribution for the survival component. We also incorporate finite mixture of normal distribution assumptions to account for the unobserved heterogeneity in the shared random effects model. A Bayesian MCMC is developed for parameter estimation and inferences. The proposed method is evaluated using simulation studies and the Tehran Lipid and Glucose Study dataset.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Bayesian paradigm; bent-cable mixed model; heterogeneity; joint modelling; mixture distributions |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 20 Jan 2025 14:50 |
Last Modified: | 20 Jan 2025 14:51 |
URI: | http://repository.essex.ac.uk/id/eprint/39968 |
Available files
Filename: A Bayesian joint bent-cable model for longitudinal measurements and survival time with heterogeneous random-effects distributions.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0