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Axinn says data show incidents of sexual assault start at 'very young age'

Miech on 'generational forgetting' about drug-use dangers

Impacts of H-1B visas: Lower prices and higher production - or lower wages and higher profits?

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Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

ICPSR Summer Program scholarships to support training in statistics, quantitative methods, research design, and data analysis

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Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Spatial Dynamics of the Local Built Environment in the City of Chicago: An Investigation of Data Sources and Methods

Archived Abstract of Former PSC Researcher

Download PDF versionBader, Michael, and Jennifer Ailshire. 2008. "Spatial Dynamics of the Local Built Environment in the City of Chicago: An Investigation of Data Sources and Methods." PSC Research Report No. 08-663. 12 2008.

Recent studies have demonstrated the importance of the local built environment on individual health outcomes. Further investigation of key theoretical issues, namely improved conceptualization of potential causal mechanisms and the definition of neighborhood boundaries, is hindered by issues of measurement. Using innovative data collected from systematic social observations of a sample (N=1,663) blocks in the city of Chicago, we adapt the geostatistical method of kriging used in environmental and material sciences to demonstrate how the spatial autocorrelation of observations in the social environment can be used to create both nuanced and geographically comprehensive measures the built environment. We validate kriging as a method of estimating the physical condition of buildings on city blocks and use measured based on this estimation to investigate the association between the physical conditions of buildings on self-rated health. We discuss the implications for data collection and analysis of neighborhood effects on health and suggest possible extensions using other innovative methods of measurement.

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