USING THE SEYCHELLES CHILD DEVELOPMENT STUDY TO CLUSTER MULTIPLE OUTCOMES INTO DOMAINS TO IMPROVE ESTIMATION OF THE OVERALL EFFECT OF MERCURY ON NEURODEVELOPMENT

摘要

Environmental exposure effects on human development can be small and difficult to detect due to the nature of observational data. In the Seychelles Child Development Study, researchers examined the effect of prenatal methylmercury exposure using a battery of tests measuring aspects of child development [, ]. We build a multiple outcomes model similar to that of the previous analyses (see [, ]); however, our multiple outcomes model makes no assumptions of relationships between the testing outcomes. Instead, the nesting of outcomes into domains is a clustering problem we address with a Dirichlet process mixture model implemented through a Bayesian MCMC approach []. This model provides inference for the methylmercury exposure effect as well as greater insight into the similarities and differences across the outcomes.