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

Directed acyclic graphs (DAGs), which offer systematic representations of causal relationships, have become an established framework for the analysis of causal inference in epidemiology, often being used to determine covariate adjustment sets for minimizing confounding bias. DAGitty is a popular web...

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Vydané v:International journal of epidemiology Ročník 45; číslo 6; s. 1887 - 1894
Hlavní autori: Textor, Johannes, van der Zander, Benito, Gilthorpe, Mark S, Liskiewicz, Maciej, Ellison, George Th
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England 01.12.2016
Predmet:
Bias
Causality
Confounding Factors (Epidemiology)
Data Interpretation, Statistical
Epidemiologic Methods
Humans
Software
ISSN:1464-3685
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Shrnutí:Directed acyclic graphs (DAGs), which offer systematic representations of causal relationships, have become an established framework for the analysis of causal inference in epidemiology, often being used to determine covariate adjustment sets for minimizing confounding bias. DAGitty is a popular web application for drawing and analysing DAGs. Here we introduce the R package 'dagitty', which provides access to all of the capabilities of the DAGitty web application within the R platform for statistical computing, and also offers several new functions. We describe how the R package 'dagitty' can be used to: evaluate whether a DAG is consistent with the dataset it is intended to represent; enumerate 'statistically equivalent' but causally different DAGs; and identify exposure-outcome adjustment sets that are valid for causally different but statistically equivalent DAGs. This functionality enables epidemiologists to detect causal misspecifications in DAGs and make robust inferences that remain valid for a range of different DAGs. The R package 'dagitty' is available through the comprehensive R archive network (CRAN) at [https://cran.r-project.org/web/packages/dagitty/]. The source code is available on github at [https://github.com/jtextor/dagitty]. The web application 'DAGitty' is free software, licensed under the GNU general public licence (GPL) version 2 and is available at [http://dagitty.net/].
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1464-3685
DOI:10.1093/ije/dyw341