Modeling Frailty Using Birnbaum Saunders Distribution for Bivariate Survival Data

Authors

Lal Pawimawha^*,

Department of Statistics, Pachhunga University College, Mizoram, 796001, India

^*Corresponding author. Email: raltelalpawimawha08@gmail.com

DOI

10.2991/jsta.d.210222.001How to use a DOI?

Keywords

Bayesian model comparison; Birnbaum–Saunders frailty; Exponential power distribution; Pareto distribution; Shared frailty; Weibull distribution

Abstract

Frailty models are survival models, which are designed to explore the properties of the unobserved heterogeneity in individuals pertaining to disease and death. In this paper, we propose the new frailty model called Birnbaum–Saunders frailty model with Weibull, Pareto, and exponential power as baseline distributions. Estimation of the proposed model parameters was done using Bayesian estimation procedure under Markov chain Monte Carlo technique. A simulation study was also presented to compare the true values and the estimated parameters. We then applied these proposed models to kidney infection data. Models comparison was done using various information criteria and Bayes factor. The best model for the data related to infection occur due to insertion of catheter is suggested.

Copyright

© 2021 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Lal Pawimawha
PY  - 2021
DA  - 2021/03/12
TI  - Modeling Frailty Using Birnbaum Saunders Distribution for Bivariate Survival Data
JO  - Journal of Statistical Theory and Applications
SP  - 355
EP  - 363
VL  - 20
IS  - 2
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.210222.001
DO  - 10.2991/jsta.d.210222.001
ID  - Pawimawha2021
ER  -