Gamma shared frailty model based on reversed hazard rate. (English) Zbl 1341.62272
Summary: Frailty models are used in survival analysis to account for unobserved heterogeneity in individual risks to disease and death. To analyze bivariate data on related survival times (e.g., matched pairs experiments, twin, or family data), shared frailty models were suggested. Shared frailty models are frequently used to model heterogeneity in survival analysis. The most common shared frailty model is a model in which hazard function is a product of random factor(frailty) and baseline hazard function which is common to all individuals. There are certain assumptions about the baseline distribution and distribution of frailty. In this paper, we introduce shared gamma frailty models with reversed hazard rate. We introduce Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in the model. We present a simulation study to compare the true values of the parameters with the estimated values. Also, we apply the proposed model to the Australian twin data set.
MSC:
| 62N01 | Censored data models |
| 62F15 | Bayesian inference |
| 62P10 | Applications of statistics to biology and medical sciences; meta analysis |
Keywords:
Bayesian estimation; gamma frailty; generalized exponential distribution; left censoring; MCMC; reversed hazard rate; shared frailtyReferences:
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