期刊
JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH
卷 58, 期 4, 页码 265-271出版社
BMJ PUBLISHING GROUP
DOI: 10.1136/jech.2002.006361
关键词
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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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