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.

Meeting Name

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)


Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2015 Elsevier Ltd, All rights reserved.

Publication Date

01 May 2015