Adjustment for time-invariant and time-varying confounders in ‘unexplained residuals’ models for longitudinal data within a causal framework and associated challenges

Arnold, KF orcid.org/0000-0002-0911-5029, Ellison, GTH orcid.org/0000-0001-8914-6812, Gadd, SC et al. (4 more authors) (2018) Adjustment for time-invariant and time-varying confounders in ‘unexplained residuals’ models for longitudinal data within a causal framework and associated challenges. Statistical Methods in Medical Research. ISSN 0962-2802

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018, The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Keywords: unexplained residuals model; conditional regression model; conditional analysis; conditional growth; conditional weight; conditional size; directed acyclic graph; causal inference; lifecourse epidemiology
Dates:
  • Accepted: 8 January 2018
  • Published (online): 16 February 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Healthcare (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 10 Jan 2018 16:47
Last Modified: 23 Apr 2018 20:38
Status: Published online
Publisher: SAGE Publications
Identification Number: https://doi.org/10.1177/0962280218756158

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