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Analysis of Bivariate Survival Data using Shared Inverse Gaussian Frailty Model

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  • David D. Hanagal
  • Richa Sharma

Abstract

In this article, we consider shared frailty model with inverse Gaussian distribution as frailty distribution and log-logistic distribution (LLD) as baseline distribution for bivariate survival times. We fit this model to three real-life bivariate survival data sets. The problem of analyzing and estimating parameters of shared inverse Gaussian frailty is the interest of this article and then compare the results with shared gamma frailty model under the same baseline for considered three data sets. Data are analyzed using Bayesian approach to the analysis of clustered survival data in which there is a dependence of failure time observations within the same group. The variance component estimation provides the estimated dispersion of the random effects. We carried out a test for frailty (or heterogeneity) using Bayes factor. Model comparison is made using information criteria and Bayes factor. We observed that the shared inverse Gaussian frailty model with LLD as baseline is the better fit for all three bivariate data sets.

Suggested Citation

  • David D. Hanagal & Richa Sharma, 2015. "Analysis of Bivariate Survival Data using Shared Inverse Gaussian Frailty Model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(7), pages 1351-1380, April.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:7:p:1351-1380
    DOI: 10.1080/03610926.2013.768663
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    Cited by:

    1. Bodunrin Brown & Bin Liu & Stuart McIntyre & Matthew Revie, 2023. "Reliability evaluation of repairable systems considering component heterogeneity using frailty model," Journal of Risk and Reliability, , vol. 237(4), pages 654-670, August.
    2. David D. Hanagal, 2021. "RETRACTED ARTICLE: Positive Stable Shared Frailty Models Based on Additive Hazards," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(3), pages 431-453, December.
    3. Aymen Rawashdeh & Mohammed Hassan Al-Haj Ebrahem & Ayat Momani, 2018. "A Bayesian approach to estimate the failure time distribution of a log-logistic degradation model," METRON, Springer;Sapienza Università di Roma, vol. 76(2), pages 155-176, August.

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