Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects Epidemiology
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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…
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1Topics & keywords
Topics
Keywords
- Confounding
- Odds ratio
- Confidence interval
- Epidemiology
- Medicine
- Odds
- Causality (physics)
- Statistics
UN Sustainable Development Goals
- Good health and well-being
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