A flexible parametric competing-risks model using a direct likelihood approach for the cause-specific cumulative incidence function

Sarwar Islam Mozumder (), Mark J. Rutherford () and Paul C. Lambert ()
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Sarwar Islam Mozumder: University of Leicester
Mark J. Rutherford: University of Leicester
Paul C. Lambert: University of Leicester

Stata Journal, 2017, vol. 17, issue 2, 462-489

Abstract: In competing-risks analysis, the cause-specific cumulative incidence function (CIF) is usually obtained in a modeling framework by either 1) transform- ing on all cause-specific hazards or 2) transforming by using a direct relationship with the subdistribution hazard function. We expand on current competing-risks methodology from within the flexible parametric survival modeling framework and focus on the second approach. This approach models all cause-specific CIFs si- multaneously and is more useful for answering prognostic-related questions. We propose the direct flexible parametric survival modeling approach for the cause- specific CIF. This approach models the (log cumulative) baseline hazard without requiring numerical integration, which leads to benefits in computational time. It is also easy to make out-of-sample predictions to estimate more useful measures and incorporate alternative link functions, for example, logit links. To implement these methods, we introduce a new estimation command, stpm2cr, and demon- strate useful predictions from the model through an illustrative melanoma dataset.

Keywords: stpm2cr; survival analysis; competing risks; flexible parametric models; subdistribution hazard; cumulative incidence function (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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