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

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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Metadata

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.
Venue
Psychosomatic Medicine
Published
2004-11
Volume
66
Issue
6
Pages
868-875
ISSN
0033-3174 (ISSN-L)
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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