- Title
- Application of correspondence analysis to graphically investigate associations between foods and eating locations
- Creator
- Chapman, Andrew N.; Beh, Eric J.; Palla, Luigi
- Relation
- Studies in Health Technology and Informatics Vol. 235, p. 166-170
- Publisher Link
- http://dx.doi.org/10.3233/978-1-61499-753-5-166
- Publisher
- IOS Press
- Resource Type
- journal article
- Date
- 2017
- Description
- This paper presents the application of correspondence analysis (CA) for investigating associations using confidence regions (CRs) with a focus on facilitating mining the data and hypothesis generation. We study the relationship between locations and “less-healthy” food consumption by UK teenagers. CA allows for a quick visual inspection of the various association structures that exist between the categories of cross-classified variables in large datasets derived with varying study designs. The hypotheses generated by the visual display can then be independently tested using suitable regression models. CA makes use of readily available software tools and of robust statistical tests amenable to interpretation.
- Subject
- correspondence analysis; confidence regions; hypothesis generation; hypothesis testing; clustered data; hierarchic data; location; food-group; healthy
- Identifier
- http://hdl.handle.net/1959.13/1349429
- Identifier
- uon:30401
- Identifier
- ISSN:0926-9630
- Rights
- © 2017 European Federation for Medical Informatics (EFMI) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
- Language
- eng
- Full Text
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