Poverty and InequalitySexual and Reproductive HealthFamily, Maternal & Child HealthMethodology

Reconciling statistical and systems science approaches to public health

TitleReconciling statistical and systems science approaches to public health
Publication TypeJournal Article
Year of Publication2013
AuthorsIp, EH, Rahmandad, H, Shoham, DA, Hammond, R, Huang, TT, Wang, Y, Mabry, PL
JournalHealth Education & Behavior : The Official Publication of the Society for Public Health Education
Date PublishedOct
ISBN Number1552-6127 (Electronic)1090-1981 (Linking)
Accession Number24084395
Keywords*Models, Statistical, Child, Data Interpretation, Statistical, Humans, Obesity/epidemiology/*prevention & control/therapy, Parent-Child Relations, peer group, Public Health/*methods/statistics & numerical data, Social Support, Systems Theory

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.