Mamas Mamas m.mamas@keele.ac.uk
Investigating Heterogeneity of Effects and Associations Using Interaction Terms
Mamas
Authors
Abstract
Effect heterogeneity, the variability of an association or exposure across subgroups, usually warrants further investigation. The aim of this deeper analysis is to identify effect modifiers (or moderators) and quantify their relationship with the exposure. We explain why it is better to harness interaction effects within a single analytic model than to use separate models to analyse each subgroup. Using examples, we demonstrate a practical approach to modelling and interpretation with interaction terms from various measurement scales (categorical by categorical; categorical by continuous; and continuous by continuous).
Acceptance Date | Sep 15, 2017 |
---|---|
Publication Date | Jan 1, 2018 |
Journal | Journal of Clinical Epidemiology |
Print ISSN | 0895-4356 |
Publisher | Elsevier |
Pages | 79-83 |
DOI | https://doi.org/10.1016/j.jclinepi.2017.09.012 |
Keywords | interaction terms, effect heterogeneity, effect modifiers, split-sample |
Publisher URL | https://doi.org/10.1016/j.jclinepi.2017.09.012 |
Files
Interactions manuscript v7.0.docx
(81 Kb)
Document
Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search