期刊
CURRENT EPIDEMIOLOGY REPORTS
卷 7, 期 4, 页码 203-211出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s40471-020-00245-2
关键词
Difference in difference; Change scores; Causal inference; John Snow
资金
- NIH/NICHD [K01 HD100222-01A1]
Purpose of Review The goal of this article is to provide an introduction to the intuition behind the difference-in-difference method for epidemiologists. We focus on the theoretical aspects of this tool, including the types of questions for which difference-in-difference is appropriate, and what assumptions must hold for the results to be causally interpretable. Recent Findings While currently under-utilized in epidemiologic research, the difference-in-difference method is a useful tool to examine effects of population level exposures, but relies on strong assumptions. We use the famous example of John Snow's investigation of the cause of cholera mortality in London to illustrate the difference-in-difference approach and corresponding assumptions. We conclude by arguing that this method deserves a second look from epidemiologists interested in asking causal questions about the impact of a population level exposure change on a population level outcome for the group that experienced the change.
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