Data Analysis Papers
Analysis of Data from Recurrent Events
Gordon Johnston and Ying So, SAS Institute, 2003.
Abstract
Time-to-event data have long been important in many applied fields. Many models and analysis methods have been developed for this type of data, in which each sample unit experiences at most a single endof- life event. In contrast, many applications involve repeated events, where a subject or sample unit may experience any number of events over a lifetime. There is a growing interest in the analysis of recurrent events data, also called repeated events data and recurrence data. This type of data arises in many fields. For example, the repair history of manufactured items can be modeled as recurrent events. In medical studies, the times of recurrent disease episodes in patients can also be modeled as recurrent events. This paper describes methods for the analysis of recurrent events data. Nonparametric methods involving extensive use of graphics for the analysis of such data are discussed in a new book by Nelson (2003). These methods are illustrated using the SAS/QC? RELIABILITY procedure. The use of the SAS/STAT? GENMOD and PHREG procedures to fit regression models to recurrent events data is also illustrated. Examples are presented from the fields of medical studies and product reliability.