A Practical Guide to Selection Bias in Instrumental Variable Analyses
Abstract
From the Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. Editor’s Note: A related article appears on p. 350. Supported by an NWO/ZonMW (Netherlands Organization for Scientific Research) Veni Grant (91617066). Disclosure: The author reports no conflicts of interest. Correspondence: Sonja A. Swanson, Department of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands. E-mail: [email protected].
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
When selection bias is a concern, researchers also frequently conduct simulations to understand the plausible size and direction of bias.
“When selection bias is a concern, researchers also frequently conduct simulations to understand the plausible size and direction of bias.64”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [64]
Cites
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816 · see citing works
Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922 · see citing works
Causal Diagrams for Epidemiologic Research
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00008 · Cited by 3,728 · cited 1× · see citing works
“We illustrate key points with exemplar causal diagrams; readers unfamiliar with causal diagrams are encouraged to consult other resources to learn more.(12) Moreover, given the ubiquity of Mendelian randomization analyses (i.”
BackgroundAir 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 · cited 1× · see citing works
“Indeed, one threat to the validity of IV analyses is selection or collider stratification bias.(1) While the possibility of selection bias is clear in many of the seminal papers on IV methods,(2,3) the relevant nuances and subtleties have been lost in translation to the more frequent end-users of IV methods.”
BackgroundMaternal 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
Hernán, M. A., Sauer, B. C., Hernández-Díaz, S., Platt, R., & Shrier, I. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2016.04.014 · Cited by 1,097 · see citing works
Instruments for Causal Inference: An Epidemiologist's Dream?
Hernán, M. A., & Robins, J. M. (2006) · Epidemiology · doi:10.1097/01.ede.0000222409.00878.37 · Cited by 961 · see citing works
Correcting for non-compliance in randomized trials using structural nested mean models
Robins, J. M. (1994) · Communication in Statistics- Theory and Methods · doi:10.1080/03610929408831393 · Cited by 534 · see citing works
Glymour, M. M., Tchetgen Tchetgen, E. J., & Robins, J. M. (2012) · American Journal of Epidemiology · doi:10.1093/aje/kwr323 · Cited by 292 · see citing works
Swanson, S. A., Tiemeier, H., Ikram, M. A., & Hernán, M. A. (2017) · Epidemiology · doi:10.1097/ede.0000000000000699 · Cited by 202 · see citing works
Self-citationLabrecque, J., & Swanson, S. A. (2018) · Current Epidemiology Reports · doi:10.1007/s40471-018-0152-1 · Cited by 190 · see citing works
Self-citationSwanson, S. A., Hernán, M. A., Miller, M., Robins, J. M., & Richardson, T. S. (2018) · Journal of the American Statistical Association · doi:10.1080/01621459.2018.1434530 · Cited by 93 · see citing works
Self-citationHughes, R. A., Davies, N. M., Davey Smith, G., & Tilling, K. (2019) · Epidemiology · doi:10.1097/ede.0000000000000972 · Cited by 89 · see citing works
Selecting on Treatment: A Pervasive Form of Bias in Instrumental Variable Analyses
Swanson, S. A., Robins, J. M., Miller, M., & Hernán, M. Á. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwu284 · Cited by 69 · see citing works
Self-citationInstrumental Variable Analyses and Selection Bias
Canan, C. E., Lesko, C. R., & Lau, B. M. (2017) · Epidemiology · doi:10.1097/ede.0000000000000639 · Cited by 65 · see citing works
Swanson, S. A., Labrecque, J. A., & Hernán, M. Á. (2018) · European Journal of Epidemiology · doi:10.1007/s10654-018-0396-6 · Cited by 40 · see citing works
Self-citationMendelian randomization studies in the elderly
Boef, A. G. C., le Cessie, S., & Dekkers, O. M. (2015) · Epidemiology · doi:10.1097/ede.0000000000000243 · Cited by 39 · see citing works
Ertefaie, A., Small, D. S., Flory, J., & Hennessy, S. (2016) · The International Journal of Biostatistics · doi:10.1515/ijb-2015-0006 · Cited by 27 · see citing works
A Sensitivity Analysis to Assess Bias Due to Selecting Subjects Based on Treatment Received
Ertefaie, A., Small, D. S., Flory, J., et al. (2015) · Epidemiology · doi:10.1097/ede.0000000000000430 · Cited by 12 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Skrivankova, V. W., Richmond, R. C., Woolf, B. A. R., Davies, N. M., Swanson, S. A., VanderWeele, T. J., Timpson, N. J., Higgins, J. P. T., Dimou, N., Langenberg, C., et al. (2021) · BMJ · doi:10.1136/bmj.n2233 · Cited by 1,648 · see citing works
Self-citationSchooling, C. M., Lopez, P. M., Yang, Z., Zhao, J. V., Au Yeung, S. L., & Huang, J. V. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2020.610852 · Cited by 102 · see citing works
Mendelian randomisation approaches to the study of prenatal exposures: A systematic review
Diemer, E. W., Labrecque, J. A., Neumann, A., Tiemeier, H., & Swanson, S. A. (2021) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12691 · Cited by 21 · see citing works
Self-citationDiemer, E. W., Labrecque, J., Tiemeier, H., & Swanson, S. A. (2020) · Epidemiology · doi:10.1097/ede.0000000000001126 · Cited by 19 · see citing works
Self-citation
- Authors
- Swanson, S. A.
- Affiliations
- Erasmus MC (NL)
- Corresponding author
- Swanson, Sonja A.
- ORCID
- Swanson, Sonja A.
- Venue
- Epidemiology
- Published
- 2019-05
- Volume
- 30
- Issue
- 3
- Pages
- 345-349
- ISSN
- 1044-3983 (ISSN-L)
- OpenAlex
- W2936600185
- Cited by
- 36
- References
- 20
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 4 · 2023: 8 · 2022: 5 · 2021: 8 · 2020: 3 · 2019: 1
- FWCI
- 3.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (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
- selection bias, instrumental variables, endogeneity, causal inference, omitted variable bias, confounding
- MeSH terms
- Epidemiologic Methods, Humans, Selection Bias, Causality, Confounding Factors, Epidemiologic, Databases as Topic, Mendelian Randomization Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
