Indian Journal of Science and Technology
DOI: 10.17485/IJST/v16iSP2.6447
Year: 2023, Volume: 16, Issue: Special Issue 2, Pages: 30-37
Original Article
Kuki Kalpita Mahanta1*, Jiten Hazarika2
1Assistant Professor, Department of Statistics, Dibrugarh University, Dibrugarh, Assam, India
2Professor, Department of Statistics, Dibrugarh University, Dibrugarh, Assam, India
*Corresponding Author
Email: [email protected]
Received Date:23 March 2023, Accepted Date:26 June 2023, Published Date:02 November 2023
Objectives: The objective of this study is to develop a new Proportional Odds frailty model by using a Weibull hazard function in context of Bayesian mechanism. Methods: Frailty models provide a convenient way to introduce random effects, association and unobserved heterogeneity into models for survival data. Proportional Odds (PO) model is a widely pursued model in survival analysis which extends the concept of Odds ratio considered for lifetime data with covariates. Proportional Odds models can be derived under frailty approach by introducing a frailty term for each individual in the exponent of the hazard function, which acts multiplicatively on the baseline hazard function. In this paper an attempt has been made to develop a new Proportional Odds frailty model by using a Weibull hazard function in context of Bayesian mechanism. Findings: The methodologies are applied to a real life survival data set and the posterior inferences are drawn using Markov Chain Monte Carlo (MCMC) simulation methods and model comparison tools like Deviance Information Criteria (DIC) and the Log Pseudo Marginal Likelihood (LPML) are also calculated and to check the fit of the model Cox-Snell residual plot is employed. The performance of the newly developed model is compared with an existing proportional odds model without the frailty term and it is observed that the newly developed frailty model perform well as compered to the traditional non frailty model. Novelty: A new Proportional Odds frailty model using Weibull hazard function under Bayesian mechanism is developed in this paper which is an added contribution in the field of Survival Analysis.
Keywords: Proportional Odds (PO) model, Frailty, MCMC simulation methods, DIC, LPML, Cox Snell residual plot
© 2023 Mahanta & Hazarika. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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