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Extending the flexible parametric survival model for competing risks

Author

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  • Sally R. Hinchliffe

    (University of Leicester)

  • Paul C. Lambert

    (University of Leicester)

Abstract

Competing risks are present when the patients within a dataset could experience one or more of several exclusive events and the occurrence of any one of these could impede the event of interest. One of the measures of interest for analyses of this type is the cumulative incidence function. stpm2cif is a postestimation command used to generate predictions of the cumulative incidence function after fitting a flexible parametric survival model using stpm2. There is also the option to generate confidence intervals, cause-specific hazards, and two other measures that will be discussed in further detail. The new command is illustrated through a simple example. Copyright 2013 by StataCorp LP.

Suggested Citation

  • Sally R. Hinchliffe & Paul C. Lambert, 2013. "Extending the flexible parametric survival model for competing risks," Stata Journal, StataCorp LP, vol. 13(2), pages 344-355, June.
    • Handle: RePEc:tsj:stataj:y:13:y:2013:i:2:p:344-355
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    References listed on IDEAS

    as
    1. Paul C. Lambert & Patrick Royston, 2009. "Further development of flexible parametric models for survival analysis," Stata Journal, StataCorp LP, vol. 9(2), pages 265-290, June.
    2. Enzo Coviello, 2009. "Covariate-adjusted cumulative incidence in the presence of competing risks," Italian Stata Users' Group Meetings 2009 02, Stata Users Group.
    3. Vincenzo Coviello & May Boggess, 2004. "Cumulative incidence estimation in the presence of competing risks," Stata Journal, StataCorp LP, vol. 4(2), pages 103-112, June.
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    Cited by:

    1. Manuela Stranges & François-Charles Wolff, 2018. "From hell to heaven? Evidence of migration trajectories from an Italian refugee centre," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(36), pages 963-990.

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