Statistical Indices for Risk Tracking in Longitudinal Studies

The ability to track a subject’s risk factors and health outcomes over time is one of the main advantages of longitudinal studies over the simpler cross-sectional studies. An important issue of time-trend tracking is to define appropriate statistical indices to quantitatively measure the tracking abilities of variables of interest over time. We review in this paper a number of local statistical tracking indices derived from the conditional distributions, and propose a series of global statistical tracking indices based on the weighted means of the corresponding local tracking indices. We investigate the statistical properties of the new global tracking indices in a simulation study, and demonstrate the usefulness of these tracking indices through their application to a longitudinal study of cardiovascular risk factors for children and adolescents.

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