Seminar
Kiros Berhane, Ph.D.
"Flexible Models for Multiple Longitudinal Outcomes: A move towards integration"
We propose a flexible multi-level modeling technique that to model multiple longitudinal outcomes of mixed type. This work is motivated by our desire to study the long term effects of air pollution on children's health by examining the relationship between ecologic covariates (e.g. air pollution) and functionals related to various nonlinear lung function growth curves, and asthma related outcomes. The latent variable approach is used in connecting the outcomes within a subject. This technique allows for the estimation of cluster specific growth curves, after adjusting for subject-specific growth-curve parameters. A Gibbs sampling approach is implemented to obtain posterior mean and variance estimates of non-linear functionals of growth curves in a unified way. Ecologic inference is then conducted in a multi level setting. We illustrate the technique via analysis of data from the Southern California Children's Health Study.