Correlated Gamma Frailty Model Based on Logistic Exponential Baseline Distribution

A.Pandey ¹ , Lalpawimawha ² , S.Bhushan ³ , P.K. Misra⁴

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.6 , pp.170-176, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v5i6.170176

Online published on Dec 31, 2018

Copyright © A.Pandey, Lalpawimawha, S.Bhushan, P.K. Misra . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
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. Shared frailty models are used despite their limitations. To overcome their disadvantages correlated frailty models may be used. In this paper, we propose correlated gamma frailty model with logistic exponential distribution as baseline distribution to analyze real-life bivariate survival dataset of McGilchrist and Aisbett [9] related to kidney infection. The Bayesian approach of Markov Chain Monte Carlo was employed to estimate the parameters involved in the models and modles comparison was done by using Bayesian comparison techniques such as Akaike information criteria (AIC), Bayesian information criteria (BIC), Deviance information criteria (DIC) and Bayes factor. Simulation study also carried out to compare the true values of parameters and estimated values of the parameters. A better model suggested for the data.

Key-Words / Index Term :
Bayesian model comparison, Correlated gamma frailty,Logistic exponential distribution, MCMC

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