Invited Commentary: Selection Bias Without Colliders
Open accessAbstract
In causal analyses, conditioning on a collider generally results in selection bias. Conditioning on a prognostic factor that is independent of the exposure—and therefore is not a collider—can also result in selection bias when 1) the exposure has a non-null effect on the outcome and 2) the association between the noncollider and the outcome is heterogenous across levels of the exposure. This result was empirically demonstrated by Greenland in 1977 (Am J Epidemiol. 1977;106(3):184–187).
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Most studies recruit survivors of the original birth cohorts, so all participants must have survived to observe the outcome; selection on surviving genetic make-up and the outcome or a competing risk effectively applies covariable adjustment on survival into the estimates.
“In addition, most studies recruit survivors of the original birth cohorts. This means all participants must have survived in order to observe whether they get the outcome of interest. Selection of participants on surviving their genetic make-up and the outcome of interest or a competing risk of the outcome effectively applies covariable adjustment on survival into the estimates.173–175”
From Mendelian randomization (2022) · cites this paper as [173]
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Causal Diagrams for Epidemiologic Research
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00008 · Cited by 3,728 · see citing works
Air Pollution and Hospital Admissions for Heart Disease in Eight U.S. Counties
Schwartz, J. D. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00005 · Cited by 3,044 · see citing works
A structural approach to selection bias
Hernán, M. A., Hernández-Díaz, S., & Robins, J. M. (2004) · Epidemiology · doi:10.1097/01.ede.0000135174.63482.43 · Cited by 2,844 · see citing works
Self-citationCausal diagrams for empirical research
PEARL, J. (1995) · Biometrika · doi:10.1093/biomet/82.4.669 · Cited by 2,355 · cited 1× · see citing works
“The application of the rules of d-separation (4) to Figure 2 shows that E and D are independent whether the analysis includes all individuals in the population (no box around C) or is restricted to the uncensored individuals (box around C); that is, no selection bias arises when the sharp null hypothesis holds—the exp…”
MethodMaternal Pesticide Exposure from Multiple Sources and Selected Congenital Anomalies
Shaw, G. M., Wasserman, C. R., O’Malley, C. D., Nelson, V. E., & Jackson, R. J. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00011 · Cited by 1,783 · see citing works
RESPONSE AND FOLLOW-UP BIAS IN COHORT STUDIES
Greenland, S. (1977) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a112451 · Cited by 264 · see citing works
Adjustments and their Consequences-Collapsibility Analysis using Graphical Models
Greenland, S., & Pearl, J. (2011) · International Statistical Review · doi:10.1111/j.1751-5823.2011.00158.x · Cited by 94 · see citing works
A Comparison of Agent-Based Models and the Parametric G-Formula for Causal Inference
Murray, E. J., Robins, J. M., Seage, G. R., Freedberg, K. A., & Hernán, M. Á. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx091 · Cited by 70 · see citing works
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Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., Palmer, T., Schooling, C. M., Wallace, C., Zhao, Q., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00092-5 · Cited by 2,229 · see citing works
Collider bias undermines our understanding of COVID-19 disease risk and severity
Griffith, G. J., Morris, T. T., Tudball, M. J., Herbert, A., Mancano, G., Pike, L., Sharp, G. C., Sterne, J., Palmer, T. M., Davey Smith, G., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19478-2 · Cited by 826 · see citing works
Target Validity and the Hierarchy of Study Designs
Westreich, D., Edwards, J. K., Lesko, C. R., Cole, S. R., & Stuart, E. A. (2019) · American Journal of Epidemiology · doi:10.1093/aje/kwy228 · Cited by 165 · see citing works
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Hughes, R. A., Davies, N. M., Davey Smith, G., & Tilling, K. (2019) · Epidemiology · doi:10.1097/ede.0000000000000972 · Cited by 89 · see citing works
Early postpartum physical activity and pelvic floor support and symptoms 1 year postpartum
Nygaard, I. E., Wolpern, A., Bardsley, T., Egger, M. J., & Shaw, J. M. (2021) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2020.08.033 · Cited by 48 · see citing works
- Authors
- Hernán, M. A.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-05-23
- Volume
- 185
- Issue
- 11
- Pages
- 1048-1050
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- PMC
- PMC6664806
- OpenAlex
- W2617954971
- Cited by
- 116
- References
- 8
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 15 · 2023: 12 · 2022: 18 · 2021: 14 · 2020: 12 · 2019: 9 · 2018: 9 · 2017: 1
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Journal of Epidemiology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (NIH R01 AI102634)
- 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
- selection bias, collider bias, prognostic factors, treatment effect heterogeneity, causal inference, exposure-outcome association
- MeSH terms
- Humans, Models, Theoretical, Epidemiologic Research Design, Selection Bias, Causality
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