Cited by 172Advanced Causal Inference TechniquesStatistical Methods and InferenceStatistical Methods in Epidemiology

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On model selection and model misspecification in causal inference.

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Vansteelandt, Stijn, Bekaert, Maarten, Claeskens, Gerda·2012·Statistical Methods in Medical Research

DOI 10.1177/0962280210387717

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Abstract

Standard variable selection procedures, primarily developed for the construction of outcome prediction models, are routinely applied when assessing exposure effects in observational studies. We argue that this tradition is sub-optimal and prone to yield bias in exposure effect estimators as well as their corresponding uncertainty estimators. We weigh the pros and cons of confounder-selection procedures and propose a procedure directly targeting the quality of the exposure effect estimator. We further demonstrate that certain strategies for inferring causal effects have the desirable features (a) of producing (approximately) valid confidence intervals, even when the confounder-selection process is ignored, and (b) of being robust against certain forms of misspecification of the association of confounders with both exposure and outcome.

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Authors: Vansteelandt, S., Bekaert, M., & Claeskens, G.
Affiliations: Ghent University (BE)
KU Leuven (BE)
Corresponding author: Vansteelandt, Stijn
ORCID: Vansteelandt, Stijn
Claeskens, Gerda
Venue: Statistical Methods in Medical Research
Publisher: SAGE Publications
Published: 2010-11-12
Volume: 21
Issue: 1
Pages: 7-30
ISSN: 0962-2802 (ISSN-L)
1477-0334
DOI: 10.1177/0962280210387717
OpenAlex: W2107263285
Cited by: 172
References: 70
Citations by year: 2026: 3 · 2025: 9 · 2024: 18 · 2023: 11 · 2022: 13 · 2021: 14 · 2020: 15 · 2019: 10 · 2018: 11 · 2017: 15 · 2016: 9 · 2015: 11 · 2014: 13 · 2013: 6 · 2012: 10
FWCI: 5.41
Type: journal article
Language: en
Open access: green
doi.org
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Statistical Methods in Medical Research (publishedVersion)
SSRN Electronic Journal (acceptedVersion)
PubMed (publishedVersion)
Lirias (submittedVersion, other-oa)
Ghent University Academic Bibliography (Ghent University) (submittedVersion)
Lirias (KU Leuven) (submittedVersion)
Funders: Vlaamse regering
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: model selection, model misspecification, causal inference, confounder selection, exposure effect estimation, confidence intervals, observational studies
MeSH terms: Computer Simulation, Data Interpretation, Statistical, Cardiac Catheterization, Humans, Models, Statistical, Bias, Causality, Confounding Factors, Epidemiologic, Biomedical Research

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On model selection and model misspecification in causal inference.

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