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Confounding in longitudinal studies in addiction treatment research

Bibliographic Data

ID15398159
AuthorsMatthias Pierce (0000-0003-2182-0369, University of Manchester, corresponding author), Graham Dunn (0000-0001-7091-3161, University of Manchester), Tim Millar (0000-0003-4630-2357, University of Manchester)
Year2016
Volume25
Issue3
Pages236-242
Publication date2016-12-22
Open AccessYes
TypeARTICLE
VenueAddiction Research & Theory (JOURNAL)
Journal identifiersISSN: 1476-7392 • E-ISSN: 1606-6359
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/16066359.2016.1247812
PMID28392755
OpenAlexW2563154025
LanguageEN
Citations received1
References cited32

Background: The effectiveness of treatment for people with substance use disorders is usually examined using longitudinal cohorts. In these studies, treatment is often considered as a time-varying exposure. The aim of this commentary is to examine confounding in this context, when the confounding variable is time-invariant and when it is time-varying. Method: Types of confounding are described with examples and illustrated using path diagrams. Simulations are used to demonstrate the direction of confounding bias and the extent that it is accounted for using standard regression adjustment techniques. Results: When the confounding variable is time invariant or time varying and not influenced by prior treatment, then standard adjustment techniques are adequate to control for confounding bias, provided that in the latter scenario the time-varying form of the variable is used. When the confounder is time varying and affected by prior treatment status (i.e. it is a mediator of treatment), then standard methods of adjustment result in inconsistency. Conclusions: In longitudinal cohorts where treatment exposure is time varying, confounding is an issue which should be considered, even if treatment exposure is initially randomized. In these studies, standard methods of adjustment may result be inadequate, even when all confounders have been identified. This occurs when the confounder is also a mediator of treatment. This is a likely scenario in many studies in addiction

Addiction · Biology · Confounding · Context (archaeology · Longitudinal study · Psychiatry · Advanced Causal Inference Techniques · Health Systems, Economic Evaluations, Quality of Life · Medicine · Psychology · Statistical Methods and Bayesian Inference · Internal Medicine

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Citations per year0.13
Citation span2018 - 2018 (1)
Highly citedNo

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