In recent years different approaches for the analysis of time-to-event data in the presence of competing risks, i. e. when subjects can fail from one of two or more mutually exclusive types of event, were introduced. Different approaches for the analysis of competing risks data, focusing either on cause-specific or subdistribution hazard rates, were presented in statistical literature. Many new approaches use complicated weighting techniques or resampling methods, not allowing an analytical evaluation of these methods. Simulation studies often replace analytical comparisons, since they can be performed more easily and allow investigation of non-standard scenarios. For adequate simulation studies the generation of appropriate random numbers is essential. We present an approach to generate competing risks data following flexible prespecified subdistribution hazards. Event times and types are simulated using possibly time-dependent cause-specific hazards, chosen in a way that the generated data will follow the desired subdistribution hazards or hazard ratios, respectively.     «

In recent years different approaches for the analysis of time-to-event data in the presence of competing risks, i. e. when subjects can fail from one of two or more mutually exclusive types of event, were introduced. Different approaches for the analysis of competing risks data, focusing either on cause-specific or subdistribution hazard rates, were presented in statistical literature. Many new approaches use complicated weighting techniques or resampling methods, not allowing an analytical eval...     »