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Posterior consistency in frailty models and simulation studies to test the presence of random effects. (English) Zbl 1411.62281

Summary: The estimation of random effects in frailty models is an important problem in survival analysis. Testing for the presence of random effects can be essential to improving model efficiency. Posterior consistency in dispersion parameters and coefficients of the frailty model was demonstrated in theory and simulations using the posterior induced by Cox’s partial likelihood and simple priors. We also conducted simulation studies to test for the presence of random effects; the proposed method performed well in several simulations. Data analysis was also conducted. The proposed method is easily tractable and can be used to develop various methods for Bayesian inference in frailty models.

MSC:

62N02 Estimation in survival analysis and censored data
62N03 Testing in survival analysis and censored data
62J02 General nonlinear regression
62F15 Bayesian inference
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