An application of longitudinal methods to the analysis of menstrual diary data

Despite the considerable morbidity associated with menstrual dysfunction and mounting evidence that women's endogenous endocrine environment influences their long term health, epidemiologic investigation of menstruation is limited. A major obstacle has been the difficulty in analyzing menstrual diary data. This paper describes the variability in menstrual cycle length in college women using a longitudinal perspective. We first characterize the distribution of cycle length and show that it can be approximated by a mixture of a nearly symmetric distribution centered at 28 days and a stochastically larger component which produces a long right tail. After assessing the degree of heterogeneity in cycling patterns, we propose an analytical approach that examines cycle lengths within the symmetric portion of the distribution and cycle lengths within the tail of the distribution separately using random effects models.