Bayesian Models for Multiple Outcomes in Domains With Application to the Seychelles Child Development Study

• Published in: Journal of the American Statistical Association Vol. 109; no. 505; pp. 1 - 10
• Main Authors: Xiao, Luo, Thurston, Sally W., Ruppert, David, Love, Tanzy M. T., Davidson, Philip W.
• Format: Journal Article
• Language: English
• Published: United States Taylor & Francis 2014; Taylor & Francis Group, LLC; Taylor & Francis Ltd
• Subjects: Applications and Case Studies; Bayesian analysis; Bayesian networks; Bayesian variable selection; central nervous system; Child development; children; Cognition; Cognitive models; Correlations; Estimation bias; Human exposure; Intelligence quotient; Latent variable model; Markov chain Monte Carlo; Memory; Mercury; Methylmercury; methylmercury compounds; Motor ability; Nervous system; Reason; Seychelles; Simulations; social behavior; Sparsity; Statistics; Seychelles; Bayesian variable selection; Latent variable model; Sparsity; Markov chain Monte Carlo; Methylmercury

The Seychelles Child Development Study (SCDS) examines the effects of prenatal exposure to methylmercury on the functioning of the central nervous system. The SCDS data include 20 outcomes measured on 9-year-old children that can be classified broadly in four outcome classes or "domains":...