Research Summary

Modeling multiple pollutants at multiple sites, with application to acute respiratory studies
Jon Wakefield
Aim of research: To develop models for pollution measures taken at multiple sites.

Data: The primary data are on seven pollutants from 23 sites in London over the period 1981--1997. Meteorological data are also available. The secondary data set is on PM$_10$ only from 15 sites in the greater Seattle area over the period 1990-1995.

Methods: The pollutants will be modeled using Bayesian dynamic generalized linear models. Specifically the framework of state space models will be used with the observed pollution level being modeled as arising from some true underlying level, but corrupted with measurement error. These true underlying levels are assumed to have structure both in space and time. Under this framework, missing data will be automatically imputed which, in particular, is useful for the analysis of health studies.