Confounder Selection: Objectives and Approaches
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Abstract (arXiv)
Confounder selection is perhaps the most important step in the design of observational studies. A number of criteria, often with different objectives and approaches, have been proposed, and their validity and practical value have been debated in the literature. Here, we provide a unified review of these criteria and the assumptions behind them. We list several objectives that confounder selection methods aim to achieve and discuss the amount of structural knowledge required by different approaches. Finally, we discuss limitations of the existing approaches and implications for practitioners.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Aug 2022.
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Citing papers per year: 2024: 3; 2025: 1.
4 papers.
- 2024Local Causal Discovery for Structural Evidence of Direct Discriminationcited by 6
- 2024Efficient adjustment for complex covariates: Gaining efficiency with DOPEcited by 5
- 2024Off-policy Evaluation with Deeply-abstracted Statescited by 2
- 2025A Graphical Approach to State Variable Selection in Off-policy Learningcited by 1
- 2025A Graphical Approach to State Variable Selection in Off-policy Learning1 Jan 2025
- 2024Off-policy Evaluation with Deeply-abstracted States27 Jun 2024
- 2024Local Causal Discovery for Structural Evidence of Direct Discrimination23 May 2024
- 2024Efficient adjustment for complex covariates: Gaining efficiency with DOPE20 Feb 2024