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Updated: Jun 1, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Understanding competing risks: a simulation point of view
Arthur Allignol1, Martin Schumacher, Christoph Wanner
1Freiburg Center for Data Analysis and Modeling, University of Freiburg, Germany. arthur.allignol@fdm.uni-freiburg.de
Background:
Competing risks methodology allows for an event-specific analysis of the single components of composite time-to-event endpoints. A key feature of competing risks is that there are as many hazards as there are competing risks. This is not always well accounted for in the applied literature.
Methods:
We advocate a simulation point of view for understanding competing risks. The hazards are envisaged as momentary event forces. They jointly determine the event time. Their relative magnitude determines the event type. 'Empirical simulations' using data from a recent study on cardiovascular events in diabetes patients illustrate subsequent interpretation. The method avoids concerns on identifiability and plausibility known from the latent failure time approach.
Results:
The 'empirical simulations' served as a proof of concept. Additionally manipulating baseline hazards and treatment effects illustrated both scenarios that require greater care for interpretation and how the simulation point of view aids the interpretation. The simulation algorithm applied to real data also provides for a general tool for study planning.
Conclusions:
There are as many hazards as there are competing risks. All of them should be analysed. This includes estimation of baseline hazards. Study planning must equally account for these aspects.
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