The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Reducing bias through directed acyclic graphs
Open accessAbstract
BACKGROUND: The objective of most biomedical research is to determine an unbiased estimate of effect for an exposure on an outcome, i.e. to make causal inferences about the exposure. Recent developments in epidemiology have shown that traditional methods of identifying confounding and adjusting for confounding may be inadequate. DISCUSSION: The traditional methods of adjusting for "potential confounders" may introduce conditional associations and bias rather than minimize it. Although previous published articles have discussed the role of the causal directed acyclic graph approach (DAGs) with respect to confounding, many clinical problems require complicated DAGs and therefore investigators may continue to use traditional practices because they do not have the tools necessary to properly use the DAG approach. The purpose of this manuscript is to demonstrate a simple 6-step approach to the use of DAGs, and also to explain why the method works from a conceptual point of view. SUMMARY: Using the simple 6-step DAG approach to confounding and selection bias discussed is likely to reduce the degree of bias for the effect estimate in the chosen statistical model.
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“Covariate selection for the regression analysis was guided by a directed acyclic graph (DAG) [7], which included age at hospitalization and sex (Appendix 4).”
From Pediatric traumatic brain injury and later psychotic syndromes in Finland (2025) · cites this paper as [7]
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Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
Marginal Structural Models and Causal Inference in Epidemiology
Robins, J. M., Hernán, M. Á., & Brumback, B. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00011 · Cited by 5,581
Statistics and Causal Inference
Holland, P. W. (1986) · Journal of the American Statistical Association · doi:10.1080/01621459.1986.10478354 · Cited by 5,293
Causation, Prediction, and Search
Spirtes, P., Glymour, C., & Scheines, R. (2001) · doi:10.7551/mitpress/1754.001.0001 · Cited by 4,521
Causal Diagrams for Epidemiologic Research
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00008 · Cited by 3,728
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
Hernan, M. A. (2002) · American Journal of Epidemiology · doi:10.1093/aje/155.2.176 · Cited by 1,445
Toward a Clearer Definition of Confounding
Weinberg, C. R. (1993) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116591 · Cited by 401
Can DAGs Clarify Effect Modification?
Weinberg, C. R. (2007) · Epidemiology · doi:10.1097/ede.0b013e318126c11d · Cited by 94
Cited by
Robust causal inference using directed acyclic graphs: the R package ‘dagitty’
Textor, J., van der Zander, B., Gilthorpe, M. S., Liśkiewicz, M., & Ellison, G. T. H. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyw341 · Cited by 2,295
Risk of arrhythmias in 52 755 long-distance cross-country skiers: a cohort study
Andersen, K., Farahmand, B., Ahlbom, A., Held, C., Ljunghall, S., Michaëlsson, K., & Sundström, J. (2013) · European Heart Journal · doi:10.1093/eurheartj/eht188 · Cited by 448
Causal inference and longitudinal data: a case study of religion and mental health
VanderWeele, T. J., Jackson, J. W., & Li, S. (2016) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-016-1281-9 · Cited by 322
Viner, R. M., Gireesh, A., Stiglic, N., Hudson, L. D., Goddings, A.-L., Ward, J. L., & Nicholls, D. E. (2019) · The Lancet Child & Adolescent Health · doi:10.1016/s2352-4642(19)30186-5 · Cited by 295
Gascon, M., Casas, M., Morales, E., Valvi, D., Ballesteros-Gómez, A., Luque, N., Rubio, S., Monfort, N., Ventura, R., Martínez, D., et al. (2015) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2014.09.030 · Cited by 261
Metadata
- Authors
- Shrier, I., & Platt, R. W.
- Venue
- BMC Medical Research Methodology
- Published
- 2008-10-30
- Volume
- 8
- Issue
- 1
- Pages
- 70-70
- ISSN
- 1471-2288 (ISSN-L)
- OpenAlex
- W2089198100
- Cited by
- 1,386
- References
- 9
- FWCI
- 10.24
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
