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Regression analysis of censored data using pseudo-observations


  • Erik T. Parner

    () (University of Aarhus)

  • Per K. Andersen

    () (University of Copenhagen)


We draw upon a series of articles in which a method based on pseu- dovalues is proposed for direct regression modeling of the survival function, the restricted mean, and the cumulative incidence function in competing risks with right-censored data. The models, once the pseudovalues have been computed, can be fit using standard generalized estimating equation software. Here we present Stata procedures for computing these pseudo-observations. An example from a bone marrow transplantation study is used to illustrate the method.

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  • Erik T. Parner & Per K. Andersen, 2010. "Regression analysis of censored data using pseudo-observations," Stata Journal, StataCorp LP, vol. 10(3), pages 408-422, September.
  • Handle: RePEc:tsj:stataj:v:10:y:2010:i:3:p:408-422
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    References listed on IDEAS

    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.
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    Cited by:

    1. Govert E. Bijwaard & Mikko Myrskylä & Per Tynelius & Finn Rasmussen, 2017. "Educational gain in cause-specific mortality: accounting for confounders," MPIDR Working Papers WP-2017-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    2. H. Joseph Newton & Nicholas J. Cox, 2013. "The Stata Journal Editors' Prize 2013: Erik Thorlund Parner and Per Kragh Andersen," Stata Journal, StataCorp LP, vol. 13(4), pages 669-671, December.
    3. Bijwaard, Govert & Myrskylä, Mikko & Tynelius, Per & Rasmussen, Finn, 2016. "Education, Cognitive Ability and Cause-Specific Mortality: A Structural Approach," IZA Discussion Papers 10137, Institute for the Study of Labor (IZA).


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