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A GENERALIZED BACK-DOOR CRITERION
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DOI：10.1214/14-AOS1295.png)
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摘要
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We generalize Pearl's back-door criterion for directed acyclic graphs (DAGs) to more general types of graphs that describe Markov equivalence classes of DAGs and/or allow for arbitrarily many hidden variables. We also give easily checkable necessary and sufficient graphical criteria for the existence of a set of variables that satisfies our generalized back-door criterion, when considering a single intervention and a single outcome variable. Moreover, if such a set exists, we provide an explicit set that fulfills the criterion. We illustrate the results in several examples. R-code is available in the R-package pcalg.
Keyword:
Causal inference
covariate adjustment
hidden confounders
DAG
CPDAG
MAG
PAG
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3.7
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2.8K
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2.9W
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