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Confounding of Three Binary-Variable Counterfactual Model with DAG
School of Mathematics and System Sciences, Beihang University, Beijing, China
School of Mathematics and System Sciences, Beihang University, Beijing, China
- 1 School of Mathematics and System Sciences, Beihang University, Beijing, China
- 2 School of Mathematics and System Sciences, Beihang University, Beijing, China
Applied Mathematics·Volume 04 (2013)·Pages 1397–1404·Published 25 September 2013·DOI10.4236/am.2013.410189
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Abstract
Confounding of three binary-variable counterfactual model with directed acyclic graph (DAG) is discussed in this paper. According to the effect between the control variable and the covariate variable, we investigate three causal counterfactual models: the control variable is independent of the covariate variable, the control variable has the effect on the covariate variable and the covariate variable affects the control variable. Using the ancillary information based on conditional independence hypotheses and ignorability, the sufficient conditions to determine whether the covariate variable is an irrelevant factor or whether there is no confounding in each counterfactual model are obtained.
KeywordsCausal EffectIndependence HypothesisCounterfactual ModelConfounding BiasIrrelevantAncillary InformationDirected Acyclic Graph
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