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Correlated Frailty Models Based on Reversed Hazard

  • David D. HanagalEmail author
Chapter
Part of the Industrial and Applied Mathematics book series (INAMA)

Abstract

The correlated frailty model is the important concept in the area of multivariate frailty models. In the 13th chapter, we have discussed the properties of the correlated gamma frailty and correlated inverse Gaussian frailty models based on hazard rate. Now, in this chapter, we will discuss correlated gamma frailty models based on reversed hazard rate with three different baseline distributions and also applied to Australian twin data.

References

  1. Duffy, D.L., Martin, N.G., Mathews, J.D.: Appendectomy in Australian twins. Aust. J. Hum. Genet. 47(3), 590–592 (1990)Google Scholar
  2. Hanagal, D.D.: Modeling Survival Data Using Frailty Models. Chapman and Hall, New York (2011)CrossRefGoogle Scholar
  3. Hanagal, D.D.: Correlated inverse Gaussian frailty models based on reversed hazard rate. Preprint, unpublished work (2019)Google Scholar
  4. Hanagal, D.D., Pandey, A.: Correlated gamma frailty models for bivariate survival data based on reversed hazard rate. Int. J. Data Sci. 2(4), 301–324 (2017)CrossRefGoogle Scholar
  5. Kheiri, S., Kimber, A., Meshkani, M.R.: Bayesian analysis of an inverse Gaussian correlated frailty model. Comput. Stat. Data Anal. 51, 5317–5326 (2007)MathSciNetCrossRefGoogle Scholar
  6. Pickles, A., Crouchley, R., Simonoff, E., Eaves, L., Meyer, J., Rutter, M., Hewit, J., Silberg, J.: Survival models for developmental genetic data: age at onset of puberty and antisocial behaviour in twins. Genet. Epidemiol. 11, 155–170 (1994)CrossRefGoogle Scholar
  7. Wienke, A.: Frailty Models in Survival Analysis. CRC Press, New York (2011)Google Scholar
  8. Yashin, A.I., Vaupel, J.W., Iachine, I.A.: Correlated individual frailty: an advantageous approach to survival analysis of bivariate data. Working Paper Series: Population Studies of Aging 7, CHS, Odense University, Denmark (1993)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Symbiosis Statistical InstituteSymbiosis International UniversityPuneIndia

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