For each of several individuals a sequence of repeated events, forming a renewal process, is observed up to some censoring time. The object is to estimate the average interevent time over the population of individuals as well as the variation of interevent times within and between individuals. Medical motivation comes from gastroenterology, and concerns the occurrence of certain cyclic movements in the small bowel during the fasting state. Two statistical models are considered: one is the standard variance component model adapted to censored data, and the other is a recent intensity based model with a random proportionality factor representing interindividual variation. These models are applied to the motility data, and their advantages are discussed. The intensity based model allows simple empirical Bayes estimation of the expected interevent times for an individual in the presence of censoring.