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Modeling heterogeneity for bivariate survival data by the compound Poisson distribution with random scale

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  • Hanagal, David D.

Abstract

We propose a bivariate Weibull regression model with heterogeneity (frailty or random effect) which is generated by compound Poisson distribution with random scale. We assume that the bivariate survival data follow bivariate Weibull of Hanagal (2004). There are some interesting situations like survival times in genetic epidemiology, dental implants of patients and twin births (both monozygotic and dizygotic) where genetic behavior (which is unknown and random) of patients follows a known frailty distribution. These are the situations which motivate us to study this particular model. We propose a two stage maximum likelihood estimation procedure for the parameters in the proposed model and develop large sample tests for testing significance of regression parameters.

Suggested Citation

  • Hanagal, David D., 2010. "Modeling heterogeneity for bivariate survival data by the compound Poisson distribution with random scale," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1781-1790, December.
    • Handle: RePEc:eee:stapro:v:80:y:2010:i:23-24:p:1781-1790
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    References listed on IDEAS

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    1. David Hanagal, 2009. "Weibull extension of bivariate exponential regression model with different frailty distributions," Statistical Papers, Springer, vol. 50(1), pages 29-49, January.
    2. Hanagal, David D., 2008. "Modelling heterogeneity for bivariate survival data by the log-normal distribution," Statistics & Probability Letters, Elsevier, vol. 78(9), pages 1101-1109, July.
    3. Hanagal David D., 2004. "Parametric Bivariate Regression Analysis Based on Censored Samples: A Weibull Model," Stochastics and Quality Control, De Gruyter, vol. 19(1), pages 83-90, January.
    4. Hanagal David D., 2006. "Weibull Extension of Bivariate Exponential Regression Model with Gamma Frailty for Survival Data," Stochastics and Quality Control, De Gruyter, vol. 21(2), pages 261-270, January.
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    Cited by:

    1. 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 "RETRACTED ARTICLE: Positive Stable Shared Frailty Models Based on Additive Hazards," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol.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.

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