Estimating causal effects of air quality regulations using principal stratification for spatially correlated multivariate intermediate outcomes.

ABSTRACT: Methods for causal inference regarding health effects of air quality regulations are met with unique challenges because (1) changes in air quality are intermediates on the causal pathway between regulation and health, (2) regulations typically affect multiple pollutants on the causal pathway towards health, and (3) regulating a given location can affect pollution at other locations, that is, there is interference between observations. We propose a principal stratification method designed to examine causal effects of a regulation on health that are and are not associated with causal effects of the regulation on air quality. A novel feature of our approach is the accommodation of a continuously scaled multivariate intermediate response vector representing multiple pollutants. Furthermore, we

SUBMITTER: Zigler CM 

PROVIDER: S-EPMC3297824 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature