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A First Passage Time Model for Long-Term Survivors with Competing Risks

Author

Listed:
  • Xu Ruimin

    (University of Guelph)

  • McNicholas Paul D

    (University of Guelph)

  • Desmond Anthony F

    (University of Guelph)

  • Darlington Gerarda A

    (University of Guelph)

Abstract

We investigate a competing risks model, using the specification of the Gompertz distribution for failure times from competing causes and the inverse Gaussian distribution for failure times from the cause of interest. The expectation-maximization algorithm is used for parameter estimation and the model is applied to real data on breast cancer and melanoma. In these applications, our models compare favourably with existing techniques. The proposed method provides a useful technique that may be more broadly applicable than existing alternatives.

Suggested Citation

  • Xu Ruimin & McNicholas Paul D & Desmond Anthony F & Darlington Gerarda A, 2011. "A First Passage Time Model for Long-Term Survivors with Competing Risks," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-15, May.
    • Handle: RePEc:bpj:ijbist:v:7:y:2011:i:1:n:26
    DOI: 10.2202/1557-4679.1224
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    References listed on IDEAS

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    1. Martin G. Larson & Gregg E. Dinse, 1985. "A Mixture Model for the Regression Analysis of Competing Risks Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 34(3), pages 201-211, November.
    2. Jeremy Balka & Anthony Desmond & Paul McNicholas, 2011. "Bayesian and likelihood inference for cure rates based on defective inverse Gaussian regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(1), pages 127-144.
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