Shared Gamma Frailty Models Based on Additive Hazards

被引：0

作者：

Hanagal D.D. ^{[1
]}

Pandey A. ^{[2
]}

机构：

[1] Department of Statistics, University of Pune, Pune

[2] Department of Statistics, Pachhunga University College, Aizawl

来源：

Journal of the Indian Society for Probability and Statistics | 2016年 / 17卷 / 2期

关键词：

Additive hazard rate; Bayesian model comparison; Gamma frailty; Generalised log-logistic distribution; Generalized Weibull distribution; MCMC; Shared frailty;

D O I：

10.1007/s41096-016-0011-7

中图分类号：

学科分类号：

摘要：

Frailty models are used in the survival analysis to account for the unobserved heterogeneity in individual risks to disease and death. To analyze the bivariate data on related survival times (e.g. matched pairs experiments, twin or family data), the shared frailty models were suggested. These models are based on the assumption that frailty act multiplicatively to hazard rate. In this paper we assume that frailty acts additively to hazard rate. We introduce the shared gamma frailty models with two different baseline distributions namely, the generalized log logistic and the generalized Weibull. We introduce the Bayesian estimation procedure using Markov Chain Monte Carlo technique to estimate the parameters involved in these models. We apply these models to a real life bivariate survival data set of McGilchrist and Aisbett (Biometrics 47:461–466, 1991) related to the kidney infection data and a better model is suggested for the data. © 2016, The Indian Society for Probability and Statistics (ISPS).

引用

页码：161 / 184

页数：23

共 51 条

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