|
|||||
|
|
Gamma shared frailty model based on reversed hazard rate for bivariate survival data |
|
| Affiliation: | 1. Indian Statistical Institute, New Delhi, India;2. Department of Statistics, Razi University, Kermanshah, Iran;1. Department of Computer Science, University of Oxford, United Kingdom;2. Delft Center for Systems & Control, Delft University of Technology, The Netherlands;3. Delft Institute of Applied Mathematics, Delft University of Technology, The Netherlands;1. Mathematical Institute, University of Wrocław, pl. Grunwaldzki 2/4, 50-384 Wrocław, Poland;2. Department of Actuarial Science, University of Lausanne, UNIL-Dorigny, 1015 Lausanne, Switzerland |
| Abstract: | The unknown or unobservable risk factors in the survival analysis cause heterogeneity between the individuals. Frailty models are used in the survival analysis to account for the unobserved heterogeneity in the individual risks to disease and death. In this paper, we suggest the shared gamma frailty model with the reversed hazard rate. We introduce the Bayesian estimation procedure using MCMC technique to estimate the parameters involved in the model and compare the frailty model with the baseline model. We apply the proposed models to Australian twin data set and suggest a better model. |
| Keywords: | Bayesian estimation Generalized log–logistic distribution MCMC Reversed hazard rate Shared gamma frailty |
| 本文献已被 ScienceDirect 等数据库收录！ | |