Multiblock redundancy analysis: interpretation tools and application in epidemiology
Version of Record online: 29 APR 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Journal of Chemometrics
Volume 25, Issue 9, pages 467–475, September 2011
How to Cite
Bougeard, S., Qannari, E. M. and Rose, N. (2011), Multiblock redundancy analysis: interpretation tools and application in epidemiology. J. Chemometrics, 25: 467–475. doi: 10.1002/cem.1392
- Issue online: 27 SEP 2011
- Version of Record online: 29 APR 2011
- Manuscript Accepted: 7 FEB 2011
- Manuscript Revised: 28 JAN 2011
- Manuscript Received: 5 NOV 2010
- Generalized Canonical Analysis;
- multiblock PLS;
- multiblock Redundancy Analysis;
For the purpose of exploring and modeling the relationships between a dataset Y and several datasets () measured on the same individuals, multiblock Partial Least Squares is a regression technique which is widely used, particularly in process monitoring, chemometrics and sensometrics. In the same vein, a new multiblock method, called multiblock Redundancy Analysis, is proposed. It is introduced by maximizing a criterion that reflects the objectives to be addressed. The solution of this maximization problem is directly derived from the eigenanalysis of a matrix. In addition, this method is related to other multiblock methods. Multiblock modeling methods provide to the user a large spectrum of interpretation indices for the investigation of the relationships among variables and among datasets. They are related to the criterion to maximize and therefore directly derived from the maximization problem under consideration. The interest of multiblock Redundancy Analysis and the associated interpretation tools are illustrated using a dataset in the field of veterinary epidemiology. Copyright © 2011 John Wiley & Sons, Ltd.