• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.241-250
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• 2015

An important scientific objective of longitudinal studies involves tracking the probability of a subject having certain health condition over the course of the study. Proper definitions and estimates of disease risk tracking have important implications in the design and analysis of long-term biomedical studies and in developing guidelines for disease prevention and intervention. We study in this paper a class of rank-tracking probabilities to describe a subject's conditional probabilities of having certain health outcomes at two different time points. Linear mixed effects models are considered to estimate the tracking probabilities and their ratios of interest. We apply our methods to an epidemiological study of childhood cardiovascular risk factors.