Principles of confounder selection
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Abstract
Selecting an appropriate set of confounders for which to control is critical for reliable causal inference. Recent theoretical and methodological developments have helped clarify a number of principles of confounder selection. When complete knowledge of a causal diagram relating all covariates to each other is available, graphical rules can be used to make decisions about covariate control. Unfortunately, such complete knowledge is often unavailable. This paper puts forward a practical approach to confounder selection decisions when the somewhat less stringent assumption is made that knowledge is available for each covariate whether it is a cause of the exposure, and whether it is a cause of the outcome. Based…
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1Topics & keywords
Topics
Keywords
- Covariate
- Causal inference
- Confounding
- Outcome (game theory)
- Inference
- Selection (genetic algorithm)
- Econometrics
- Selection bias
UN Sustainable Development Goals
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