Project Details
Description
PROJECT NARRATIVE
Causal inference theory and methods are indispensable to biostatistics, but due to complications such as spatial
correlation and spillover effects, methods applicable to spatial data are limited. In this project, we develop new
causal methods to allow researchers to extract knowledge from observational spatial data. The methods are
developed in the context of two large epidemiological studies of the effects of wildland fire smoke and preventative
measures on air pollution exposure and respiratory health outcomes.
Causal inference theory and methods are indispensable to biostatistics, but due to complications such as spatial
correlation and spillover effects, methods applicable to spatial data are limited. In this project, we develop new
causal methods to allow researchers to extract knowledge from observational spatial data. The methods are
developed in the context of two large epidemiological studies of the effects of wildland fire smoke and preventative
measures on air pollution exposure and respiratory health outcomes.
| Status | Finished |
|---|---|
| Effective start/end date | 1/4/20 → 31/1/23 |
| Links | https://projectreporter.nih.gov/project_info_details.cfm?aid=10334535 |
Funding
- National Institute of Environmental Health Sciences: US$289,186.00
- National Institute of Environmental Health Sciences: US$285,927.00
ASJC Scopus Subject Areas
- Pollution
- Statistics and Probability
- Pulmonary and Respiratory Medicine
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