Causality and causal inference in epidemiology: the need for a pluralistic approach - PubMed
- ️Fri Jan 01 2016
Causality and causal inference in epidemiology: the need for a pluralistic approach
Jan P Vandenbroucke et al. Int J Epidemiol. 2016.
Abstract
Causal inference based on a restricted version of the potential outcomes approach reasoning is assuming an increasingly prominent place in the teaching and practice of epidemiology. The proposed concepts and methods are useful for particular problems, but it would be of concern if the theory and practice of the complete field of epidemiology were to become restricted to this single approach to causal inference. Our concerns are that this theory restricts the questions that epidemiologists may ask and the study designs that they may consider. It also restricts the evidence that may be considered acceptable to assess causality, and thereby the evidence that may be considered acceptable for scientific and public health decision making. These restrictions are based on a particular conceptual framework for thinking about causality. In Section 1, we describe the characteristics of the restricted potential outcomes approach (RPOA) and show that there is a methodological movement which advocates these principles, not just for solving particular problems, but as ideals for which epidemiology as a whole should strive. In Section 2, we seek to show that the limitation of epidemiology to one particular view of the nature of causality is problematic. In Section 3, we argue that the RPOA is also problematic with regard to the assessment of causality. We argue that it threatens to restrict study design choice, to wrongly discredit the results of types of observational studies that have been very useful in the past and to damage the teaching of epidemiological reasoning. Finally, in Section 4 we set out what we regard as a more reasonable 'working hypothesis' as to the nature of causality and its assessment: pragmatic pluralism.
© The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Comment in
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Re: Causality and causal inference in epidemiology: the need for a pluralistic approach.
VanderWeele TJ, Hernán MA, Tchetgen Tchetgen EJ, Robins JM. VanderWeele TJ, et al. Int J Epidemiol. 2016 Dec 1;45(6):2199-2200. doi: 10.1093/ije/dyw162. Int J Epidemiol. 2016. PMID: 27524811 No abstract available.
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Counterfactual and interventionist approach to cure risk factor epidemiology.
Chiolero A. Chiolero A. Int J Epidemiol. 2016 Dec 1;45(6):2202-2203. doi: 10.1093/ije/dyw159. Int J Epidemiol. 2016. PMID: 27524812 No abstract available.
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Authors' Reply to: VanderWeele et al., Chiolero, and Schooling et al.
Broadbent A, Vandenbroucke J, Pearce N. Broadbent A, et al. Int J Epidemiol. 2016 Dec 1;45(6):2203-2205. doi: 10.1093/ije/dyw163. Int J Epidemiol. 2016. PMID: 27524813 Free PMC article. No abstract available.
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Causality and causal inference in epidemiology: we need also to address causes of effects.
Schooling CM, Chow CK, Au Yeung SL. Schooling CM, et al. Int J Epidemiol. 2016 Dec 1;45(6):2200-2201. doi: 10.1093/ije/dyw160. Int J Epidemiol. 2016. PMID: 27524814 No abstract available.
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Broadbent A, Vandenbroucke JP, Pearce N. Broadbent A, et al. Int J Epidemiol. 2016 Dec 1;45(6):1841-1851. doi: 10.1093/ije/dyw298. Int J Epidemiol. 2016. PMID: 28130316 Free PMC article. No abstract available.
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Commentary: On Causes, Causal Inference, and Potential Outcomes.
VanderWeele TJ. VanderWeele TJ. Int J Epidemiol. 2016 Dec 1;45(6):1809-1816. doi: 10.1093/ije/dyw230. Int J Epidemiol. 2016. PMID: 28130319 Free PMC article. No abstract available.
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Daniel RM, De Stavola BL, Vansteelandt S. Daniel RM, et al. Int J Epidemiol. 2016 Dec 1;45(6):1817-1829. doi: 10.1093/ije/dyw227. Int J Epidemiol. 2016. PMID: 28130320 Free PMC article. No abstract available.
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Commentary: Counterfactual causation and streetlamps: what is to be done?
Robins JM, Weissman MB. Robins JM, et al. Int J Epidemiol. 2016 Dec 1;45(6):1830-1835. doi: 10.1093/ije/dyw231. Int J Epidemiol. 2016. PMID: 28130321 Free PMC article. No abstract available.
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Commentary: Causal inference in epidemiology: potential outcomes, pluralism and peer review.
Weed DL. Weed DL. Int J Epidemiol. 2016 Dec 1;45(6):1838-1840. doi: 10.1093/ije/dyw229. Int J Epidemiol. 2016. PMID: 28130322 No abstract available.
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Blakely T, Lynch J, Bentley R. Blakely T, et al. Int J Epidemiol. 2016 Dec 1;45(6):1835-1837. doi: 10.1093/ije/dyw228. Int J Epidemiol. 2016. PMID: 28130323 No abstract available.
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