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

Textor, J, van der Zander, B, Gilthorpe, MS orcid.org/0000-0001-8783-7695 et al. (2 more authors) (2017) Robust causal inference using directed acyclic graphs: the R package ‘dagitty’. International Journal of Epidemiology, 45 (6). pp. 1887-1894. ISSN 0300-5771

Abstract

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Item Type: Article
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© The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association. This is a pre-copyedited, author-produced version of an article accepted for publication in International Journal of Epidemiology following peer review. The version of record Johannes Textor, Benito van der Zander, Mark S. Gilthorpe, Maciej Liśkiewicz, George T.H. Ellison; Robust causal inference using directed acyclic graphs: the R package ‘dagitty’. Int J Epidemiol 2017 dyw341. doi: 10.1093/ije/dyw341 is available online at: https://doi.org/10.1093/ije/dyw341

Dates:
  • Published: 14 January 2017
  • Published (online): 14 January 2017
  • Accepted: 10 November 2016
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 14 Dec 2016 16:19
Last Modified: 01 Feb 2019 12:33
Published Version: https://doi.org/10.0.4.69/ije/dyw341
Status: Published
Publisher: Oxford University Press
Identification Number: 10.1093/ije/dyw341
Open Archives Initiative ID (OAI ID):

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