Reconciling statistical and systems science approaches to public health Journal Article


Authors: Ip, E. H.; Rahmandad, H.; Shoham, D. A.; Hammond, R.; Huang, T. T.; Wang, Y; Mabry, P. L.
Article Title: Reconciling statistical and systems science approaches to public health
Abstract: Although systems science has emerged as a set of innovative approaches to study complex phenomena, many topically focused researchers including clinicians and scientists working in public health are somewhat befuddled by this methodology that at times appears to be radically different from analytic methods, such as statistical modeling, to which the researchers are accustomed. There also appears to be conflicts between complex systems approaches and traditional statistical methodologies, both in terms of their underlying strategies and the languages they use. We argue that the conflicts are resolvable, and the sooner the better for the field. In this article, we show how statistical and systems science approaches can be reconciled, and how together they can advance solutions to complex problems. We do this by comparing the methods within a theoretical framework based on the work of population biologist Richard Levins. We present different types of models as representing different tradeoffs among the four desiderata of generality, realism, fit, and precision.
Keywords: Public Health Sciences; Levins framework; agent-based model; childhood obesity; complex systems; computational model; social network analysis; statistical model; system dynamics model
Journal Title: Health education behavior : the official publication of the Society for Public Health Education
Volume: 40
Issue: 1 Suppl
ISSN: 1552-6127; 1090-1981
Publisher: Unknown  
Journal Place: United States
Date Published: 2013
Start Page: 123S
End Page: 31S
Language: eng
DOI/URL:
Notes: JID: 9704962; OTO: NOTNLM; ppublish