Nonparametric analysis of survival and event history data
In this chapter we study situations in which the data may be summarized by a counting process registering the occurrences of a specific event of interest or a few counting processes registering the occurrences of a few such events. One important example is the survival data situation, where one is interested in the time to a single event for each individual and the counting process is counting the number of occurrences of this event for a group of individuals. The event in question will depend on the study at hand; it may be the death of a laboratory animal, the relapse of a cancer patient, or the birth of a woman’s second child. In order to emphasize that events other than death are often of interest in the survival data situation, we will use the term event of interest to denote the event under study. However, as mentioned in Section 1.1, we will use the terms survival time and survival function also when the event of interest is something different from death.
KeywordsHazard Rate Counting Process Cumulative Hazard Compete Risk Model Martingale Central Limit Theorem
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