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Cited by 1,535Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyStatistical Methods and Inference

Principles of confounder selection

Open access
VanderWeele, Tyler J.·2019·European Journal of Epidemiology
DOI 10.1007/s10654-019-00494-6PMC PMC6447501
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Abstract

Selecting an appropriate set of confounders for which to control is critical for reliable causal inference. Recent theoretical and methodological developments have helped clarify a number of principles of confounder selection. When complete knowledge of a causal diagram relating all covariates to each other is available, graphical rules can be used to make decisions about covariate control. Unfortunately, such complete knowledge is often unavailable. This paper puts forward a practical approach to confounder selection decisions when the somewhat less stringent assumption is made that knowledge is available for each covariate whether it is a cause of the exposure, and whether it is a cause of the outcome. Based on recent theoretically justified developments in the causal inference literature, the following proposal is made for covariate control decisions: control for each covariate that is a cause of the exposure, or of the outcome, or of both; exclude from this set any variable known to be an instrumental variable; and include as a covariate any proxy for an unmeasured variable that is a common cause of both the exposure and the outcome. Various principles of confounder selection are then further related to statistical covariate selection methods.

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Authors
VanderWeele, T. J.
Affiliations
Harvard University (US)
Corresponding author
VanderWeele, Tyler J.
ORCID
VanderWeele, Tyler J.
Venue
European Journal of Epidemiology
Publisher
Springer Science and Business Media LLC
Published
2019-03-06
Volume
34
Issue
3
Pages
211-219
ISSN
  • 0393-2990 (ISSN-L)
  • 1573-7284
DOI
10.1007/s10654-019-00494-6
PMC
PMC6447501
OpenAlex
W2921495327
Cited by
1,535
References
11
Citations by year
2026: 245 · 2025: 277 · 2024: 254 · 2023: 248 · 2022: 205 · 2021: 195 · 2020: 94 · 2019: 17
FWCI
99.67
Type
journal article
Language
en
Open access
Licence
Locations
  • European Journal of Epidemiology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
Division of Cancer Epidemiology and Genetics, National Cancer Institute (R01CA222147)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Keywords
confounder selection, covariate control, causal inference, causal graphs, instrumental variables, proxy variables
MeSH terms
Humans, Research Design, Confounding Factors, Epidemiologic

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