Statistical Methods to Evaluate Health Effects Associated with Major Sources of Air Pollution: A Case-Study of Breathing Patterns During Exposure to Concentrated Boston Air particles

DOI10.1111/j.1467-9876.2008.00618.xzbMath1273.62255OpenAlexW2143529560MaRDI QIDQ3634610

Paul J. Catalano, Edgar Diaz, Margaret C. Nikolov, John J. Godleski, Brent A. Coull

Publication date: 25 June 2009

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9876.2008.00618.x

zbMATH Keywords

latent variablesreceptor modelstructural equation modelparticulate matterrespiratory responsesource apportionment

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12)

Related Items (2)

A Bayesian multivariate receptor model for estimating source contributions to particulate matter pollution using national databases ⋮ Using a latent variable model with non-constant factor loadings to examine PM_2.5 constituents related to secondary inorganic aerosols

Cites Work

• Unnamed Item
• Unnamed Item
• Multivariate Receptor Modeling for Temporally Correlated Data by Using MCMC
• Air Pollution and Mortality
• Bayesian Measures of Model Complexity and Fit
• Health Effects of Air Pollution: A Statistical Review
• An informative Bayesian structural equation model to assess source-specific health effects of air pollution
• Parameterization and Bayesian Modeling
• Linear Unmixing of Multivariate Observations

This page was built for publication: Statistical Methods to Evaluate Health Effects Associated with Major Sources of Air Pollution: A Case-Study of Breathing Patterns During Exposure to Concentrated Boston Air particles