Conclusion
As we have seen, competing risks analysis is easily accomplished with conventional software by doing a separate analysis for each event type, treating other events as censoring. The biggest drawback of competing risks analysis is the requirement that times for different event types be independent, or at least that each event be noninformative for the others. This requirement is exactly equivalent to the requirement for random censoring discussed in Chapter 2. In either case, violations can lead to substantially biased coefficient estimates.
The seriousness of this problem depends greatly on the particular application. For the leaders data set, I argued that death due to natural causes is likely to be noninformative for the risk of ...
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