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Goodness of fit tests for estimating equations based on pseudo-observations

Author

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  • Klemen Pavlič

    (University of Ljubljana)

  • Torben Martinussen

    (University of Copenhagen)

  • Per Kragh Andersen

    (University of Copenhagen)

Abstract

We study regression models for mean value parameters in survival analysis based on pseudo-observations. Such parameters include the survival probability and the cumulative incidence in a single point as well as the restricted mean life time and the cause-specific number of years lost. Goodness of fit techniques for such models based on cumulative sums of pseudo-residuals are derived including asymptotic results and Monte Carlo simulations. Practical examples from liver cirrhosis and bone marrow transplantation are also provided.

Suggested Citation

  • Klemen Pavlič & Torben Martinussen & Per Kragh Andersen, 2019. "Goodness of fit tests for estimating equations based on pseudo-observations," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 189-205, April.
  • Handle: RePEc:spr:lifeda:v:25:y:2019:i:2:d:10.1007_s10985-018-9427-6
    DOI: 10.1007/s10985-018-9427-6
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    References listed on IDEAS

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    1. 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.
    2. Eddelbuettel, Dirk & Francois, Romain, 2011. "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i08).
    3. 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.
    4. D. Y. Lin & L. J. Wei & Z. Ying, 2002. "Model-Checking Techniques Based on Cumulative Residuals," Biometrics, The International Biometric Society, vol. 58(1), pages 1-12, March.
    5. Martin Jacobsen & Torben Martinussen, 2016. "A Note on the Large Sample Properties of Estimators Based on Generalized Linear Models for Correlated Pseudo-observations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 845-862, September.
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    Cited by:

    1. Julie K. Furberg & Per K. Andersen & Sofie Korn & Morten Overgaard & Henrik Ravn, 2023. "Bivariate pseudo-observations for recurrent event analysis with terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 256-287, April.

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