Cengiz, MA and Percy, DF 2001, 'Mixed multivariate generalized linear models for assessing lower-limb arterial stenoses.' , Statistics in Medicine, 20 (11) , pp. 1663-1679.Full text not available from this repository.
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.
|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 > Business and Management Research Centre|
|Journal or Publication Title:||Statistics in Medicine|
|Depositing User:||H Kenna|
|Date Deposited:||21 Aug 2007 12:36|
|Last Modified:||29 Oct 2015 00:50|
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