Causal Diagrams for Epidemiologic Research
作者:
Sander Greenland,
Judea Pearl,
James Robins,
期刊:
Epidemiology
(OVID Available online 1999)
卷期:
Volume 10,
issue 1
页码: 37-48
ISSN:1044-3983
年代: 1999
出版商: OVID
关键词: bias;causation;confounding;epidemiologic methods;graphical methods;observational studies
数据来源: OVID
摘要:
Causal diagrams have a long history of informal use and, more recently, have undergone formal development for applications in expert systems and robotics. We provide an introduction to these developments and their use in epidemiologic research. Causal diagrams can provide a starting point for identifying variables that must be measured and controlled to obtain unconfounded effect estimates. They also provide a method for critical evaluation of traditional epidemiologic criteria for confounding. In particular, they reveal certain heretofore unnoticed shortcomings of those criteria when used in considering multiple potential confounders. We show how to modify the traditional criteria to correct those shortcomings. (Epidemiology 1999;10:37–48)
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