Cited by 260Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyMeta-analysis and systematic reviews

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Risk Factors, Confounding, and the Illusion of Statistical Control

Christenfeld, Nicholas J. S., Sloan, Richard P., Carroll, Douglas, Greenland, Sander·2004·Psychosomatic Medicine

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Abstract

When experimental designs are premature, impractical, or impossible, researchers must rely on statistical methods to adjust for potentially confounding effects. Such procedures, however, are quite fallible. We examine several errors that often follow the use of statistical adjustment. The first is inferring a factor is causal because it predicts an outcome even after "statistical control" for other factors. This inference is fallacious when (as usual) such control involves removing the linear contribution of imperfectly measured variables, or when some confounders remain unmeasured. The converse fallacy is inferring a factor is not causally important because its association with the outcome is attenuated or eliminated by the inclusion of covariates in the adjustment process. This attenuation may only reflect that the covariates treated as confounders are actually mediators (intermediates) and critical to the causal chain from the study factor to the study outcome. Other problems arise due to mismeasurement of the study factor or outcome, or because these study variables are only proxies for underlying constructs. Statistical adjustment serves a useful function, but it cannot transform observational studies into natural experiments, and involves far more subjective judgment than many users realize.

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Authors: Christenfeld, N. J. S., Sloan, R. P., Carroll, D., & Greenland, S.
Affiliations: University of California San Diego (US)
University of California, Los Angeles (US)
Corresponding author: Christenfeld, Nicholas J. S.
ORCID: Sloan, Richard P.
Greenland, Sander
Venue: Psychosomatic Medicine
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2004-11
Volume: 66
Issue: 6
Pages: 868-875
ISSN: 0033-3174 (ISSN-L)
DOI: 10.1097/01.psy.0000140008.70959.41
OpenAlex: W2065056866
Cited by: 260
References: 0
Citations by year: 2026: 6 · 2025: 6 · 2024: 8 · 2023: 5 · 2022: 11 · 2021: 21 · 2020: 15 · 2019: 17 · 2018: 7 · 2017: 4 · 2016: 13 · 2015: 8 · 2014: 14 · 2013: 14 · 2012: 28
FWCI: 1.33
Type: journal article
Language: en
Open access: closed
Locations: Psychosomatic Medicine (publishedVersion)
PubMed (publishedVersion)
University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords: confounding, statistical adjustment, causal inference, risk factors, measurement error, mediators, covariate adjustment, observational studies, natural experiment
MeSH terms: Data Interpretation, Statistical, False Positive Reactions, Humans, Research Design, Risk Factors, Reproducibility of Results, Health Behavior, Bias, Confounding Factors, Epidemiologic, Randomized Controlled Trials as Topic, Outcome Assessment, Health Care, Observation

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Risk Factors, Confounding, and the Illusion of Statistical Control

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