Causal Diagrams: Pitfalls and Tips

Causal Diagrams: Pitfalls and Tips

Graphical models are useful tools in causal inference, and causal directed acyclic graphs (DAGs) are used extensively to determine the variables for which it is sufficient to control for confounding to estimate causal effects. We discuss the following ten pitfalls and tips that are easily overlooked...

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Bibliografski detalji
Glavni autori: Etsuji Suzuki, Tomohiro Shinozaki, Eiji Yamamoto
Format: Članak
Jezik:English
Izdano: Japan Epidemiological Association 2020-04-01
Serija:Journal of Epidemiology
Teme:
bias
causal inference
causality
confounding
directed acyclic graphs
Online pristup:https://www.jstage.jst.go.jp/article/jea/30/4/30_JE20190192/_pdf

Internet

https://www.jstage.jst.go.jp/article/jea/30/4/30_JE20190192/_pdf

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