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A Geographically-aware Multilevel Analysis on the Association between Atmospheric Temperature and the Emergency and Transitional Shelter Population

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  • Castaneda, Ernesto

Abstract

Understanding the geographical distribution and correlates of special segments of the population has the potential for offering insight into human behavior. Our study examines the Emergency and Transitional Shelter Population (ETSP)—which includes what are commonly referred to as “homeless” people. We use 2010 data from two sources: United States (US) Census Bureau county-level ETSP estimates; and North America Land Data Assimilation System Phase 2 (NLDAS-2). We investigate the ecological correlates of ETSP concentration by using a geographically-aware multilevel linear model. The specific aim is to investigate if an how atmospheric temperature is related with ETSP concentration by county—after accounting for population density and percent non-Hispanic-White. We use ArcGIS® 10.1 to create a spatial weight matrix of the ten most proximal counties and use SAS® 9.3 to create an algorithm that estimates County Cluster Dyadic Averages (CCDAs). By nesting the 31,090 CCDAs over the 3,109 counties in the continental US, we find a positive and statistically significant relationship between ETSP density and atmospheric temperature. Ecological studies should continue to explore the spatial heterogeneity of the ETSP.

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  • Castaneda, Ernesto, 2017. "A Geographically-aware Multilevel Analysis on the Association between Atmospheric Temperature and the Emergency and Transitional Shelter Population," OSF Preprints 8a264, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:8a264
    DOI: 10.31219/osf.io/8a264
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