Mixed multivariate generalized linear models for assessing lower-limb arterial stenoses.

Cengiz, MA and Percy, DF ORCID: https://orcid.org/0000-0002-2733-3855 2001, 'Mixed multivariate generalized linear models for assessing lower-limb arterial stenoses.' , Statistics in Medicine, 20 (11) , pp. 1663-1679.

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Experiments and observational studies often involve gathering information on several response variables, enabling us to model their dependence on observable predictor variables. Despite associations between the response variables, they are often analysed separately using general and generalized linear models. This paper investigates applications of multivariate regression analysis to improve the accuracy of predictions and decisions, in the specific context of diagnosing arterial stenoses in human legs. Two basic models are developed for this application, using (i) four binary responses and (ii) a mixture of two binary and two normal responses. The results clearly demonstrate the potential advantages offered by this approach.

Item Type: Article
Themes: Subjects / Themes > R Medicine > R Medicine (General)
Subjects / Themes > Q Science > QA Mathematics > QA275 Mathematical Statistics
Health and Wellbeing
Subjects outside of the University Themes
Schools: Schools > Salford Business School > Salford Business School Research Centre
Journal or Publication Title: Statistics in Medicine
Refereed: Yes
ISSN: 0277-6715
Depositing User: H Kenna
Date Deposited: 21 Aug 2007 12:36
Last Modified: 27 Aug 2021 21:59
URI: https://usir.salford.ac.uk/id/eprint/266

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