Competing Risk Models
In the time-to-event analysis when more than one type of event can occur and not all are of interest, the situation of competing risks appears. In this chapter the competing risks will be defined, and the need for special statistical analysis techniques will be justified. The methodology for estimation and modeling in the presence of competing risks will be presented. The cumulative incidence function and the Fine and Gray model will be introduced as the main methods to analyze competing risks data. The cumulative incidence function will be contrasted to Kaplan-Meier method. For a deeper understanding of the modelling, the subdistribution hazard will be defined.
The importance of considering the competing risks in the process of designing a study will be emphasized, and the steps needed to be taken in the calculation will be presented. For a better understanding of the material and of the interpretation, examples will be given at each step.
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