Spatializing Area-Based Measures of Neighborhood Characteristics for Multilevel Regression Analyses: An Areal Median Filtering Approach.
Area-based measures of neighborhood characteristics simply derived from enumeration units (e.g., census tracts or block groups) ignore the potential of spatial spillover effects, and thus incorporating such measures into multilevel regression models may underestimate the neighborhood effects on heal...
| Publicado en: | Journal of Urban Health Vol. 93; no. 3; pp. 551 - 572 |
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| Autores principales: | , , |
| Formato: | journal article |
| Publicado: |
Springer Nature
Jun2016
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=115995662&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 115995662 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10993460 GMF jtl: Journal of Urban Health issn: 10993460 maglogo: N pubinfo: dt: Jun2016 vid: 93 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 115995662 10.1007/s11524-016-0051-z ppf: 551 ppct: 21 formats: fmt: @attributes: type: P size: 1.9MB tig: atl: Spatializing Area-Based Measures of Neighborhood Characteristics for Multilevel Regression Analyses: An Areal Median Filtering Approach. aug: au: Oka, Masayoshi Wong, David Wong, David W S affil: Social and Cardiovascular Epidemiology Research Group, Faculty of Medicine, University of Alcalá, Campus Universitario - Ctra. Madrid-Barcelona, Km 33,6000 28871 Alcalá de Henares Spain Department of Geography and GeoInformation Science, College of Science, George Mason University, Fairfax USA Department of Geography and GeoInformation Science, College of Science, George Mason University, Fairfax, VA, USA su: United States Neighborhoods Externalities Health behavior Public health Health status indicators Residential patterns Regression analysis Statistics sug: subj: Neighborhoods Externalities Health behavior Public health Health status indicators Residential patterns United States Health and Welfare Funds Regression analysis Statistics keyword: Area-based measures Areal data Median filter Multilevel regression analysis Spatial approach Spatial median USA Area-based measures Areal data Median filter Multilevel regression analysis Spatial approach Spatial median USA ab: Area-based measures of neighborhood characteristics simply derived from enumeration units (e.g., census tracts or block groups) ignore the potential of spatial spillover effects, and thus incorporating such measures into multilevel regression models may underestimate the neighborhood effects on health. To overcome this limitation, we describe the concept and method of areal median filtering to spatialize area-based measures of neighborhood characteristics for multilevel regression analyses. The areal median filtering approach provides a means to specify or formulate "neighborhoods" as meaningful geographic entities by removing enumeration unit boundaries as the absolute barriers and by pooling information from the neighboring enumeration units. This spatializing process takes into account for the potential of spatial spillover effects and also converts aspatial measures of neighborhood characteristics into spatial measures. From a conceptual and methodological standpoint, incorporating the derived spatial measures into multilevel regression analyses allows us to more accurately examine the relationships between neighborhood characteristics and health. To promote and set the stage for informative research in the future, we provide a few important conceptual and methodological remarks, and discuss possible applications, inherent limitations, and practical solutions for using the areal median filtering approach in the study of neighborhood effects on health. pubtype: Academic Journal doctype: journal article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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