 Causal inference from randomized trials in social epidemiologyJay S. Kaufman, Sol Kaufman and Charles Poole Social Science & Medicine, 2003, vol. 57, issue 12, 2397-2409 Abstract: Social epidemiology is the study of relations between social factors and health status in populations. Although recent decades have witnessed a rapid development of this research program in scope and sophistication, causal inference has proven to be a persistent dilemma due to the natural assignment of exposure level based on unmeasured attributes of individuals, which may lead to substantial confounding. Some optimism has been expressed about randomized social interventions as a solution to this long-standing inferential problem. We review the causal inference problem in social epidemiology, and the potential for causal inference in randomized social interventions. Using the example of a currently on-going intervention that randomly assigns families to non-poverty housing, we review the limitations to causal inference even under experimental conditions and explain which causal effects become identifiable. We note the benefit of using the randomized trial as a conceptual model, even for design and interpretation of observational studies in social epidemiology. Keywords: Causal; inference; Social; factors; Methods; Randomized; trials; Confounding (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:socmed:v:57:y:2003:i:12:p:2397-2409 Ordering information: This journal article can be ordered from Access Statistics for this article Social Science & Medicine is currently edited by Ichiro (I.) Kawachi and S.V. (S.V.) Subramanian More articles in Social Science & Medicine from Elsevier |
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