Conditioning on Post-treatment Variables

Pearl Judea ()
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Pearl Judea: Computer Science Department, University of California, Los Angeles, Los Angeles, CA 90095–1596, USA

Journal of Causal Inference, 2015, vol. 3, issue 1, 131-137

Abstract: In this issue of the Causal, Casual, and Curious column, I compare several ways of extracting information from post-treatment variables and call attention to some peculiar relationships among them. In particular, I contrast do-calculus conditioning with counterfactual conditioning and discuss their interpretations and scopes of applications. These relationships have come up in conversations with readers, students and curious colleagues, so I will present them in a question–answers format.

Keywords: causal effects; back-door condition; do-calculus; counterfactuals (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:causin:v:3:y:2015:i:1:p:131-137:n:1008

DOI: 10.1515/jci-2015-0005

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