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A definition of causal effect for epidemiological research

Journal of Epidemiology & Community Health · 2004 · Vol. 58(4) · pp. 265–271
Miguel A. Hernán

Abstract

Estimating the causal effect of some exposure on some outcome is the goal of many epidemiological studies. This article reviews a formal definition of causal effect for such studies. For simplicity, the main description is restricted to dichotomous variables and assumes that no random error attributable to sampling variability exists. The appendix provides a discussion of sampling variability and a generalisation of this causal theory. The difference between association and causation is described—the redundant expression “causal effect” is used throughout the article to avoid confusion with a common use of “effect” meaning simply statistical association—and shows why, in theory, randomisation allows the estimation of causal effects without further assumptions. The article concludes with a discussion on the limitations of randomised studies. These limitations are the reason why methods for causal inference from observational data are needed.

Funding

  • National Institutes of Health
Citations
466
FWCI
5.17
field-weighted impact
References
12
Percentile
96%
vs. same field & year
Citations per year
Cited by
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Estimating causal effects from epidemiological data
Journal of Epidemiology & Community Health · 2006 · 1,023 citations
References
Bayesian Inference for Causal Effects: The Role of Randomization
The Annals of Statistics · 1978 · 2,510 citations
Estimating causal effects of treatments in randomized and nonrandomized studies.
Journal of Educational Psychology · 1974 · 9,316 citations
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