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Survival Regression Models For Single Events And Competing Risks Based On Pseudo-Observations

Author

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  • Wycinka Ewa

    (University of Gdańsk, Faculty of Management. Gdańsk, Poland .)

  • Jurkiewicz Tomasz

    (University of Gdańsk, Faculty of Management. Gdańsk, Poland .)

Abstract

Survival data is a special type of data that measures the time to an event of interest. The most important feature of survival data is the presence of censored observations. An observation is said to be right-censored if the time of the observation is, for some reason, shorter than the time to the event. If no censoring occurs in the data, standard statistical models can be used to analyse the data. Pseudo-observations can replace censored observations and thereby allow standard statistical models to be used.

Suggested Citation

  • Wycinka Ewa & Jurkiewicz Tomasz, 2019. "Survival Regression Models For Single Events And Competing Risks Based On Pseudo-Observations," Statistics in Transition New Series, Statistics Poland, vol. 20(1), pages 171-188, March.
    • Handle: RePEc:vrs:stintr:v:20:y:2019:i:1:p:171-188:n:10
    DOI: 10.21307/stattrans-2019-010
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    References listed on IDEAS

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    1. John G. T. Watkins & Andrey L. Vasnev & Richard Gerlach, 2014. "Multiple Event Incidence And Duration Analysis For Credit Data Incorporating Non‐Stochastic Loan Maturity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 627-648, June.
    2. John P. Klein & Per Kragh Andersen, 2005. "Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function," Biometrics, The International Biometric Society, vol. 61(1), pages 223-229, March.
    3. Lore Dirick & Gerda Claeskens & Bart Baesens, 2017. "Time to default in credit scoring using survival analysis: a benchmark study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 652-665, June.
    4. Per Kragh Andersen, 2003. "Generalised linear models for correlated pseudo-observations, with applications to multi-state models," Biometrika, Biometrika Trust, vol. 90(1), pages 15-27, March.
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