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Activity Number: 226 - Causal Inference with Spatial Environmental Data
Type: Topic Contributed
Date/Time: Monday, July 29, 2019 : 2:00 PM to 3:50 PM
Sponsor: Royal Statistical Society
Abstract #304455
Title: Measurement Error, Spatial Confounding, and Changing Target Populations
Author(s): Joshua Keller*
Companies: Colorado State University
Keywords: Spatial Confounding; Measurement Error; Air Pollution; Causal Inference

Unmeasured spatial confounding and exposure measurement error are two major challenges for studies of the health impacts of outdoor environmental exposures. These issues can bias health effect estimates and their standard errors, leading to incorrect inference if the confounding and measurement error are ignored. In this talk, I will describe how applying methods for addressing these challenges can lead to implicit changes in the target population. This impacts the generalizability of the results, which is an important concern for studies investigating regional- and national-scale exposures.

Authors who are presenting talks have a * after their name.

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