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Am J Epidemiol. 2002 Jan 15;155(2):176-84.

Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology.

Author information

1
Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. miguel_hernan@post.harvard.edu

Abstract

Common strategies to decide whether a variable is a confounder that should be adjusted for in the analysis rely mostly on statistical criteria. The authors present findings from the Slone Epidemiology Unit Birth Defects Study, 1992-1997, a case-control study on folic acid supplementation and risk of neural tube defects. When statistical strategies for confounding evaluation are used, the adjusted odds ratio is 0.80 (95% confidence interval: 0.62, 1.21). However, the consideration of a priori causal knowledge suggests that the crude odds ratio of 0.65 (95% confidence interval: 0.46, 0.94) should be used because the adjusted odds ratio is invalid. Causal diagrams are used to encode qualitative a priori subject matter knowledge.

PMID:
11790682
DOI:
10.1093/aje/155.2.176
[Indexed for MEDLINE]

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