Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution

Gavin Shaddick; Matthew L. Thomas; Amelia Green; Michael Brauer; Aaron van Donkelaar; Rick Burnett; Howard H. Chang; Aaron Cohen; Rita Van Dingenen; Carlos Dora; Sophie Gumy; Yang Liu; Randall Martin; Lance A. Waller; Jason West; James V. Zidek; Annette Prüss-Ustün

doi:10.1111/rssc.12227

Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution

Gavin Shaddick, Matthew L. Thomas, Amelia Green, Michael Brauer, Aaron van Donkelaar, Rick Burnett, Howard H. Chang, Aaron Cohen, Rita Van Dingenen, Carlos Dora, Sophie Gumy, Yang Liu, Randall Martin, Lance A. Waller, Jason West, James V. Zidek, Annette Prüss-Ustün

科研成果: 期刊稿件 › 文章 › 同行评审

126 引用（Scopus）

源语言	英语
页（从-至）	231-253
页数	23
期刊	Journal of the Royal Statistical Society. Series C: Applied Statistics
卷	67
期	1
DOI	https://doi.org/10.1111/rssc.12227
出版状态	已出版 - 1月 2018

!!!ASJC Scopus Subject Areas

统计与概率
统计学、概率和不确定度

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10.1111/rssc.12227

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Shaddick, G., Thomas, M. L., Green, A., Brauer, M., van Donkelaar, A., Burnett, R., Chang, H. H., Cohen, A., Dingenen, R. V., Dora, C., Gumy, S., Liu, Y., Martin, R., Waller, L. A., West, J., Zidek, J. V., & Prüss-Ustün, A. (2018). Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution. Journal of the Royal Statistical Society. Series C: Applied Statistics, 67(1), 231-253. https://doi.org/10.1111/rssc.12227

Shaddick, G, Thomas, ML, Green, A, Brauer, M, van Donkelaar, A, Burnett, R, Chang, HH, Cohen, A, Dingenen, RV, Dora, C, Gumy, S, Liu, Y, Martin, R, Waller, LA, West, J, Zidek, JV & Prüss-Ustün, A 2018, 'Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution', Journal of the Royal Statistical Society. Series C: Applied Statistics, 卷 67, 号码 1, 页码 231-253. https://doi.org/10.1111/rssc.12227

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title = "Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution",

keywords = "Air pollution, Bayesian hierarchical modelling, Data fusion, Environmental health effects, Global burden of disease, Integrated nested Laplace approximations, Spatial modelling",

author = "Gavin Shaddick and Thomas, {Matthew L.} and Amelia Green and Michael Brauer and {van Donkelaar}, Aaron and Rick Burnett and Chang, {Howard H.} and Aaron Cohen and Dingenen, {Rita Van} and Carlos Dora and Sophie Gumy and Yang Liu and Randall Martin and Waller, {Lance A.} and Jason West and Zidek, {James V.} and Annette Pr{\"u}ss-Ust{\"u}n",

note = "Publisher Copyright: {\textcopyright} 2017 World Health Organization, Journal of the Royal Statistical Society: Series C (Applied Statistics) Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society.",

year = "2018",

month = jan,

doi = "10.1111/rssc.12227",

language = "English",

volume = "67",

pages = "231--253",

journal = "Journal of the Royal Statistical Society. Series C: Applied Statistics",

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T2 - a hierarchical approach to the global estimation of exposures to ambient air pollution

AU - Shaddick, Gavin

AU - Thomas, Matthew L.

AU - Green, Amelia

AU - Brauer, Michael

AU - van Donkelaar, Aaron

AU - Burnett, Rick

AU - Chang, Howard H.

AU - Cohen, Aaron

AU - Dingenen, Rita Van

AU - Dora, Carlos

AU - Gumy, Sophie

AU - Liu, Yang

AU - Martin, Randall

AU - Waller, Lance A.

AU - West, Jason

AU - Zidek, James V.

AU - Prüss-Ustün, Annette

N1 - Publisher Copyright: © 2017 World Health Organization, Journal of the Royal Statistical Society: Series C (Applied Statistics) Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society.

PY - 2018/1

Y1 - 2018/1

KW - Air pollution

KW - Bayesian hierarchical modelling

KW - Data fusion

KW - Environmental health effects

KW - Global burden of disease

KW - Integrated nested Laplace approximations

KW - Spatial modelling

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Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution

!!!ASJC Scopus Subject Areas

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