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  • Talebi Ghane, Elaheh  (2)
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  • 1
    Online Resource
    Online Resource
    Milano University Press ; 2023
    In:  Epidemiology, Biostatistics, and Public Health Vol. 18, No. 1 ( 2023-07-18), p. 19-33
    In: Epidemiology, Biostatistics, and Public Health, Milano University Press, Vol. 18, No. 1 ( 2023-07-18), p. 19-33
    Abstract: The observations of repeated or recurrent events occur in many longitudinal studies. Furthermore, sometimes there may exist a terminal event such as death, which is strongly correlated with recurrent events. In many situations, a fraction of subjects who will never experience the event of interest during a long follow-up period is considered to be cured. In this article, we proposed a joint frailty model in the presence of cure fraction. The dependency is modeled by shared frailty that is contained in both the recurrent andterminal events hazard functions. It allows to estimate two separate sets of parameters on the recurrent, death, and cure model. We applied the maximum likelihood method under a piecewise constant hazard function for model fitting. The proposed model is evaluated by simulation studies and an application to a breast cancer data is provided.
    Type of Medium: Online Resource
    ISSN: 2282-0930
    Language: Unknown
    Publisher: Milano University Press
    Publication Date: 2023
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  • 2
    In: Journal of Biostatistics and Epidemiology, Knowledge E DMCC, ( 2023-03-17)
    Abstract: Introduction: Recurrent event data are common in many longitudinal studies. Often, a terminating event such as death can be correlated with the recurrent event process. A shared frailty model applied to account for the association between recurrent and terminal events. In some situations, a fraction of subjects experience neither recurrent events nor death; these subjects are cured. Methods: In this paper, we discussed the Bayesian approach of a joint frailty model for recurrent and terminal events in the presence of cure fraction. We compared estimates of parameters in the Frequentist and Bayesian approaches via simulation studies in various sample sizes; we applied the joint frailty model in the presence of cure fraction with Frequentist and Bayesian approaches for breast cancer. Results: In small sample size Bayesian approach compared to Frequentist approach had a smaller standard error and mean square error, and the coverage probabilities close to nominal level of 95%. Also, in Bayesian approach, the sampling means of the estimated standard errors were close to the empirical standard error. Conclusion: The simulation results suggested that when sample size was small, the use of Bayesian joint frailty model in the presence of cure fraction led to more efficiency in parameter estimation and statistical inference.
    Type of Medium: Online Resource
    ISSN: 2383-420X , 2383-4196
    Language: Unknown
    Publisher: Knowledge E DMCC
    Publication Date: 2023
    detail.hit.zdb_id: 2806590-6
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