# Confounder Selection: Objectives and Approaches

arXiv: https://arxiv.org/abs/2208.13871 · HTML: https://mlsanity.com/paper/2208.13871/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2022.

## Built on by (most cited first, 4 of 4)

- [Local Causal Discovery for Structural Evidence of Direct Discrimination](https://mlsanity.com/paper/2405.14848/) (2024)
- [Efficient adjustment for complex covariates: Gaining efficiency with DOPE](https://mlsanity.com/paper/2402.12980/) (2024)
- [Off-policy Evaluation with Deeply-abstracted States](https://mlsanity.com/paper/2406.19531/) (2024)
- [A Graphical Approach to State Variable Selection in Off-policy Learning](https://mlsanity.com/paper/2501.00854/) (2025)

## 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.