A Multiple Additive Regression Tree Analysis of Three Exposure Measures During Hurricane Katrina

ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
Dr.. John Pine, Director, Research Institute for Environment, Energy and Economics (Creator)
Appalachian State University (ASU )
Web Site: https://library.appstate.edu/

Abstract: This paper analyses structural and personal exposure to Hurricane Katrina. Structural exposure is measured by flood height and building damage; personal exposure is measured by the locations of 911 calls made during the response. Using these variables, this paper characterizes the geography of exposure and also demonstrates the utility of a robust analytical approach in understanding health-related challenges to disadvantaged populations during recovery. Analysis is conducted using a contemporary statistical approach, a multiple additive regression tree (MART), which displays considerable improvement over traditional regression analysis. By using MART, the percentage of improvement in R-squares over standard multiple linear regression ranges from about 62 to more than 100 per cent. The most revealing finding is the modelled verification that African Americans experienced disproportionate exposure in both structural and personal contexts. Given the impact of exposure to health outcomes, this finding has implications for understanding the long-term health challenges facing this population.

Additional Information

Curtis, Andrew, Bin L., B. D. Marx, J. W. Mills and J. Pine (August 16, 2010). A multiple additive regression tree analysis of three exposure measures during Hurricane Katrina. Disasters: The Journal of Disaster Studies, Policy and Management. Vol 35 (1) pp. 19-35. [ISSN: 0361-3666] The version of record is published by Wiley and can be accessed at http://onlinelibrary.wiley.com/doi/10.1111/j.1467-7717.2010.01190.x/pdf.
Language: English
Date: 2010

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