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On the validity of covariate adjustment for estimating causal effects

On the validity of covariate adjustment for estimating causal effects
On the validity of covariate adjustment for estimating causal effects
Identifying effects of actions (treatments) on outcome variables from observational data and causal assumptions is a fundamental problem in causal inference. This identification is made difficult by the presence of confounders which can be related to both treatment and outcome variables. Confounders are often handled, both in theory and in practice, by adjusting for covariates, in other words considering outcomes conditioned on treatment and covariate values, weighed by probability of observing those covariate values. In this paper, we give a complete graphical criterion for covariate adjustment, which we term the adjustment criterion, and derive some interesting corollaries of the completeness of this criterion.
527-536
AUAI Press
Shpitser, Ilya
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VanderWeele, T.
608eaf6a-bad1-4a34-8c51-e5138b361a86
Robins, J.
0906d29d-f46f-4d69-b134-f24e55c49997
Shpitser, Ilya
4d295b9b-39e8-417f-b38d-fbb5d7df6992
VanderWeele, T.
608eaf6a-bad1-4a34-8c51-e5138b361a86
Robins, J.
0906d29d-f46f-4d69-b134-f24e55c49997

Shpitser, Ilya, VanderWeele, T. and Robins, J. (2010) On the validity of covariate adjustment for estimating causal effects. In Proceedings of the Twenty Sixth Conference on Uncertainty in Artificial Intelligence (UAI-10). AUAI Press. pp. 527-536 .

Record type: Conference or Workshop Item (Paper)

Abstract

Identifying effects of actions (treatments) on outcome variables from observational data and causal assumptions is a fundamental problem in causal inference. This identification is made difficult by the presence of confounders which can be related to both treatment and outcome variables. Confounders are often handled, both in theory and in practice, by adjusting for covariates, in other words considering outcomes conditioned on treatment and covariate values, weighed by probability of observing those covariate values. In this paper, we give a complete graphical criterion for covariate adjustment, which we term the adjustment criterion, and derive some interesting corollaries of the completeness of this criterion.

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Published date: 2010
Organisations: Statistics

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Local EPrints ID: 350578
URI: http://eprints.soton.ac.uk/id/eprint/350578
PURE UUID: 7426dd2b-65f0-4395-9299-add4bb0d69be

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Date deposited: 04 Apr 2013 14:15
Last modified: 14 Mar 2024 13:27

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Contributors

Author: Ilya Shpitser
Author: T. VanderWeele
Author: J. Robins

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