Abstract
Recurrent events are common in medical research, yet the best ways to measure their occurrence remain controversial. Moreover, the correct statistical techniques to compare the occurrence of such events across populations or treatment groups are not widely known. In both observational studies and randomised clinical trials one natural and intuitive measure of occurrence is the event rate, defined as the number of events (possibly including multiple events per person) divided by the total person-years of experience. This is often a more relevant and clinically interpretable measure of disease burden in a population than considering only the first event that occurs. Appropriate statistical tests to compare such event rates among treatment groups or populations require the recognition that some individuals may be especially likely to experience recurrent events. Straightforward approaches are available to account for this tendency in crude and stratified analyses. Recently developed regression models can appropriately examine the association of several variables with rates of recurrent events.