Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

Research article (International Journal of Epidemiology, 2016) · cited 2,290× · AI/ML
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Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

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Robust causal inference using directed acyclic graphs: the R package ‘dagitty’ is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Robust causal inference using directed acyclic graphs: the R package ‘dagitty’. Retrieved May 24, 2026, from https://4ort.xyz/entity/robust-causal-inference-using-directed-acyclic-graphs-the-r-package-dagitty
MLA “Robust causal inference using directed acyclic graphs: the R package ‘dagitty’.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/robust-causal-inference-using-directed-acyclic-graphs-the-r-package-dagitty.
BibTeX @misc{4ortxyz_robust-causal-inference-using-directed-acyclic-graphs-the-r-package-dagitty_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Robust causal inference using directed acyclic graphs: the R package ‘dagitty’}}, year = {2026}, url = {https://4ort.xyz/entity/robust-causal-inference-using-directed-acyclic-graphs-the-r-package-dagitty}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Robust causal inference using directed acyclic graphs: the R package ‘dagitty’ — https://4ort.xyz/entity/robust-causal-inference-using-directed-acyclic-graphs-the-r-package-dagitty (retrieved 2026-05-24)

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