On the use of causal criteria
Abstract
Background Two recent accounts of the use of causal criteria make opposite claims: that criteria should be used more often to avoid bias in assessments of weak associations and, in direct contrast, that criteria are scientifically invalid. Methods A recent review of the current practice of causal inference in epidemiology, as well as some more theoretical concerns, reveals errors in the two claims. Results In practice, epidemiologists often use the criteria of consistency, strength, dose-response, and biological plausibility, but not often temporality, when judging weak associations. These criteria are used for causal assessments as well as for making public health recommendations. In theory, causal criteria can be used to either refute or predict causal effects. Conclusion Research on causal inference methodology should be encouraged, including research on underlying theory, methodology, and additional systematic descriptions of how causal inference is practised. Specific research questions include: to what extent can consensus be achieved on definitions and accompanying rules of inference for criteria, the relationship of meta-analysis to the criterion of consistency, and the interrelationships of criteria such as consistency, strength of association, and biological plausibility.
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Distinguishing association from causation is a matter of inference, not proof, whether the approach is statistical or evidence-based.
“Ultimately, distinguishing association from causation is a matter of inference, not proof, whether the approach is statistical or evidencebased (Hill 1965, Weed 1997).”
From Evidence‐based evaluation of the cumulative effects of ecosystem restoration (2016) · cites this paper as Weed 1997
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Malin, G. L., Morris, R. K., & Khan, K. S. (2010) · BMJ · doi:10.1136/bmj.c1471 · Cited by 461 · see citing works
Is meta-analysis the platinum standard of evidence?
Stegenga, J. (2011) · Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences · doi:10.1016/j.shpsc.2011.07.003 · Cited by 193 · see citing works
The role of causal criteria in causal inferences: Bradford Hill's "aspects of association"
Ward, A. C. (2009) · Epidemiologic Perspectives & Innovations · doi:10.1186/1742-5573-6-2 · Cited by 120 · see citing works
“On the other side of the inductive-deductive dichotomy, it is also a mistake to claim that "causal criteria can be used to critically test – through refutation and prediction – causal hypotheses of necessary causes" [44].”
Analyzing cause and effect in environmental assessments: using weighted evidence from the literature
Norris, R. H., Webb, J. A., Nichols, S. J., Stewardson, M. J., & Harrison, E. T. (2012) · Freshwater Science · doi:10.1899/11-027.1 · Cited by 113 · see citing works
Evidence‐based evaluation of the cumulative effects of ecosystem restoration
Diefenderfer, H. L., Johnson, G. E., Thom, R. M., Buenau, K. E., Weitkamp, L. A., Woodley, C. M., Borde, A. B., & Kropp, R. K. (2016) · Ecosphere · doi:10.1002/ecs2.1242 · Cited by 49 · see citing works
Can We Establish Causality with Statistical Analyses? The Example of Epidemiology
Frick, U., & Rehm, J. (2016) · Wiley Series in Probability and Statistics · doi:10.1002/9781118947074.ch17 · Cited by 14 · see citing works
- Authors
- Weed, D.
- Affiliations
- National Cancer Institute (US)
- Corresponding author
- Weed, D.
- ORCID
- Weed, D.
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1997-12-01
- Volume
- 26
- Issue
- 6
- Pages
- 1137-1141
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- OpenAlex
- W2172295445
- Cited by
- 97
- References
- 0
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 3 · 2022: 2 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 5 · 2017: 3 · 2016: 6 · 2015: 1 · 2014: 3 · 2013: 4 · 2012: 6
- FWCI
- 3.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Sociology and Political Science › Historical and modern epidemiology studies
- Keywords
- causal criteria, causal inference, weak associations, consistency, associative strength, dose-response relationship, biological plausibility, temporality, public health recommendations, inference rules
- MeSH terms
- Epidemiologic Methods, Ethics, Medical, Humans, Philosophy, Causality
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