Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.

ABSTRACT:

Background

Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data.

Methods

We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated d

SUBMITTER: Keller JP 

PROVIDER: S-EPMC5378630 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature