Abstract

We present Bayesian models, for longitudinal data that are clustered and non-continuous (more specifically, count and ordinal). Using these newly developed models, we will undertake a comprehensive and refined statistical examination of the total accumulation of dental caries and fluorosis data obtained from Iowa Fluoride Study participants. In other words, we fit longitudinal statistical models to caries and fluorosis scores data obtained at ages five, nine, thirteen, seventeen, and twenty-three, for the participants in this cohort study of Iowa children. The ultimate goal is to study the time-varying (in particular, long-term) and joint effects of various risk and protective factors for dental caries and fluorosis outcomes.