Title: A Bayesian approach to functional-based multilevel modeling of longitudinal data: applications to environmental epidemiology.
Authors: Berhane, Kiros; Molitor, Nuoo-Ting
Published In Biostatistics, (2008 Oct)
Abstract: Flexible multilevel models are proposed to allow for cluster-specific smooth estimation of growth curves in a mixed-effects modeling format that includes subject-specific random effects on the growth parameters. Attention is then focused on models that examine between-cluster comparisons of the effects of an ecologic covariate of interest (e.g. air pollution) on nonlinear functionals of growth curves (e.g. maximum rate of growth). A Gibbs sampling approach is used to get posterior mean estimates of nonlinear functionals along with their uncertainty estimates. A second-stage ecologic random-effects model is used to examine the association between a covariate of interest (e.g. air pollution) and the nonlinear functionals. A unified estimation procedure is presented along with its computational and theoretical details. The models are motivated by, and illustrated with, lung function and air pollution data from the Southern California Children's Health Study.
PubMed ID: 18349036
MeSH Terms: Adolescent; Adolescent Development/physiology; Air Pollutants/analysis; Air Pollution/adverse effects; Air Pollution/analysis; Algorithms; Bayes Theorem; Body Height/physiology; California; Child; Child Development/physiology; Environmental Exposure/adverse effects; Environmental Exposure/statistics & numerical data*; Environmental Health/methods; Environmental Health/statistics & numerical data*; Epidemiologic Methods; Female; Forced Expiratory Volume/physiology; Humans; Linear Models; Longitudinal Studies; Lung Diseases/epidemiology; Lung Diseases/etiology; Lung Diseases/physiopathology*; Male; Models, Statistical*; Ozone/analysis; Respiratory Function Tests; Soot/analysis