Imperial College London
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DrRuiPinto

Faculty of Medicine, School of Public Health

Research Associate in Chemometrics/Metabolomics
 
 
 
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Contact

 

+44 (0)20 7594 9761r.pinto Website

 
 
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Location

 

155Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Jouan-Rimbaud:2011:10.1016/j.chemolab.2010.05.005,
author = {Jouan-Rimbaud, Bouveresse D and Pinto, RC and Schmidtke, LM and Locquet, N and Rutledge, DN},
doi = {10.1016/j.chemolab.2010.05.005},
journal = {Chemometrics and Intelligent Laboratory Systems},
pages = {173--182},
title = {Identification of significant factors by an extension of ANOVA-PCA based on multi-block analysis},
url = {http://dx.doi.org/10.1016/j.chemolab.2010.05.005},
volume = {106},
year = {2011}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - A modification of the ANOVA-PCA method, proposed by Harrington et al. to identify significant factors and interactions in an experimental design, is presented in this article. The modified method uses the idea of multiple table analysis, and looks for the common dimensions underlying the different data tables, or data blocks, generated by the "ANOVA-step" of the ANOVA-PCA method, in order to identify the significant factors. In this paper, the "Common Component and Specific Weights Analysis" method is used to analyse the calculated multi-block data set. This new method, called AComDim, was compared to the standard ANOVA-PCA method, by analysing four real data sets. Parameters computed during the AComDim procedure enable the computation of F-values to check whether the variability of each original data block is significantly greater than that of the noise. © 2010 Elsevier B.V.
AU  - Jouan-Rimbaud,Bouveresse D
AU  - Pinto,RC
AU  - Schmidtke,LM
AU  - Locquet,N
AU  - Rutledge,DN
DO  - 10.1016/j.chemolab.2010.05.005
EP  - 182
PY  - 2011///
SN  - 0169-7439
SP  - 173
TI  - Identification of significant factors by an extension of ANOVA-PCA based on multi-block analysis
T2  - Chemometrics and Intelligent Laboratory Systems
UR  - http://dx.doi.org/10.1016/j.chemolab.2010.05.005
VL  - 106
ER  -
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