The central hypothesis of this study is that a holistic, systems-based approach employing multiple analytical tools is useful for identifying the most sensitive links within complex communities to down-scale global development priorities such as the United Nations Sustainable Development Goals. Results of latent factor regression, canonical correlation analysis, and structural equation modeling were compared for multiple, publically-available data sets for two rural regions in Brazil and Guatemala. The results of this study confirm previously reported findings, and collectively support the central hypothesis demonstrating a pathway for linking global priorities with the complex realities of 'on-the-ground' development conditions in specific communities.
L. E. Voth-Gaeddert and D. B. Oerther, "Measuring Multidimensional Poverty in a Complex Environment; Identifying the Sensitive Links," Procedia Engineering, vol. 107, pp. 172-180, Elsevier Ltd, May 2015.
The definitive version is available at http://dx.doi.org/10.1016/j.proeng.2015.06.071
Humanitarian Technology: Science, Systems and Global Impact, HumTech 2015 (2015: May 12-14, Boston, MA)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Correlation methods; Factor analysis; Large scale systems; Analytical tool; Canonical correlation analysis; Complex environments; Complex reality; Global development; Latent factor; multidimensional poverty; Structural equation modeling; Sustainable development; complex systems; latent factor regression
International Standard Serial Number (ISSN)
Article - Conference proceedings
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