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Survival data analysis is traditionally focused on analyzing lifetimes by using time that is measured to an event of interest, or the latest time available if the event did not occur during the observation period. Data measured in this way are called right-censored data. Many methods (nonparametric, semiparametric, and fully parametric) have been developed over the years to deal with this type of data. But what methods are available if the event time is not directly observed and the event is known only to have occurred within some interval of time? Data measured in this way are called interval-censored survival data, and the use of SAS software to analyze this type of data is the focus of this paper.
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