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March 16, 2004Journal of Epidemiology & Community Health477 citationsOpen Access

A definition of causal effect for epidemiological research

MHMiguel A. Hernán

Key Points

  • The aim is to provide a formal definition of causal effect relevant to epidemiological research.
  • Focused on dichotomous variables and excluded random error from sampling variability.
  • Discussed differences between association and causation.
  • Provided a generalisation of causal theory in the appendix.
  • Clarified that randomisation can estimate causal effects without additional assumptions.
  • Described limitations of randomised studies that necessitate methods for causal inference from observational data.

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.

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Cite This Study

Miguel A. Hernán (2004) studied this question.

synapsesocial.com/papers/69d7d05fba18484428d17feahttps://doi.org/10.1136/jech.2002.006361
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