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Article

On the estimation of hazard rate in mixed populations with its application

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Pages 7564-7575 | Received 24 Aug 2020, Accepted 22 Feb 2022, Published online: 09 Mar 2022

References

  • Aktekin, T. 2014. Call center service process analysis: Bayesian parametric and semi-parametric mixture modeling. European Journal of Operational Research 234 (3):709–19. doi:10.1016/j.ejor.2013.10.064.
  • Andersen, P. K., and R. D. Gill. 1982. Cox’s regression model for counting processes: A large sample study. The Annals of Statistics 10 (4):1100–20. doi:10.1214/aos/1176345976.
  • Block, H. W., and T. H. Savits. 1997. Burn-in. Statistical Science 12 (1):1–19. doi:10.1214/ss/1029963258.
  • Farewell, V. T. 1982. The use of mixture models for the analysis of survival data with long-term survivors. Biometrics 38 (4):1041–6. doi:10.2307/2529885.
  • Finkelstein, M. 2008. Failure rate modelling for reliability and risk. London: Springer Science & Business Media.
  • Finkelstein, M. 2009. Understanding the shape of the mixture failure rate (with engineering and demographic applications). Applied Stochastic Models in Business and Industry 25 (6):643–63. doi:10.1002/asmb.815.
  • Finkelstein, M. S., and V. Esaulova. 2001. Modeling a failure rate for a mixture of distribution functions. Probability in the Engineering and Informational Sciences 15 (3):383–400. doi:10.1017/S0269964801153076.
  • Lin, D. Y. 2000. On fitting Cox’s proportional hazards models to survey data. Biometrika 87 (1):37–47. doi:10.1093/biomet/87.1.37.
  • Lynn, N. J., and N. D. Singpurwalla. 1997. [burn-in]: Comment:” burn-in” makes us feel good. Statistical Science 12 (1):13–9.
  • McLachlan, G., and D. Peel. 2004. Finite mixture models. New York: John Wiley & Sons.
  • Peng, Y., and K. B. Dear. 2000. A nonparametric mixture model for cure rate estimation. Biometrics 56 (1):237–43. doi:10.1111/j.0006-341x.2000.00237.x.
  • Pollard, D. 1990. Empirical processes: Theory and applications. Hayward, CA: Institute of Mathematical Statistics.
  • Royston, P., and M. K. Parmar. 2011. The use of restricted mean survival time to estimate the treatment effect in randomized clinical trials when the proportional hazards assumption is in doubt. Statistics in Medicine 30 (19):2409–21. doi:10.1002/sim.4274.
  • Royston, P., W. Sauerbrei, and A. Ritchie. 2004. Is treatment with interferon-α effective in all patients with metastatic renal carcinoma? a new approach to the investigation of interactions. British Journal of Cancer 90 (4):794–9. doi:10.1038/sj.bjc.6601622.
  • Schlattmann, P. 2009. Medical applications of finite mixture models. Berlin, Heidelberg: Springer.
  • Taylor, J. M. 1995. Semi-parametric estimation in failure time mixture models. Biometrics 51 (3):899–907. doi:10.2307/2532991.
  • Wang, L., P. Du, and H. Liang. 2012. Two-component mixture cure rate model with spline estimated nonparametric components. Biometrics 68 (3):726–35. doi:10.1111/j.1541-0420.2011.01715.x.
  • Zhang, J., and Y. Peng. 2009. Accelerated hazards mixture cure model. Lifetime Data Analysis 15 (4):455–67. doi:10.1007/s10985-009-9126-4.

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