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The Academia Team

A decision that must be made is whether to treat all events the same or to differentiate types of events. If the event is an arrest, for example, one could either treat all arrests the same or distinguish between arrests for misdemeanors and arrests for felonies. All deaths could be treated alike, or one could distinguish between different kinds of deaths according to reported causes. Of course, such distinctions are only possible if data are available to differentiate the event types. Why do it? Usually, it is done because there are reasons to believe that predictor variables have different effects on different event types. In such cases, the prevailing strategy is to estimate competing risks models. The downside of distinguishing different event types is that fewer events are available to estimate each set of parameters, which might substantially reduce statistical power.

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