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In the first multivariate analysis, Analysis 1 adjusted for age and gender, 7 of the frequent criteria had an OR > 3 (range 3.72 53.95).
Multivariate analysis analysis, based on PCA and LDA, together with the leave-one tissue site-out, cross validation on in vivo gastric Raman spectra yielded a sensitivity of 94.4% (17/18) and specificity of 96.3% (52/54) for distinction of gastric dysplastic tissue [ 41].
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The ELSD data were also analyzed using multivariate principal component analysis, analysis of variance, and standard least squares effects modeling.
A multivariate analysis (correspondence analysis) was done to verify resemblance between the communities.
Data were classified according to the metabolic profile using a multivariate analysis in principal component analysis.
The results generated from univariate analysis and multivariate analysis often complement each other.
For analyzing water quality data were subjected to descriptive multivariate analysis: cluster analysis (CA) and PCA/factor analysis (FA) and CA using SPSS of its version 22.0.
As a kind of dimension reduction technology in multivariate analysis, factor analysis can effectively reduce numerous data into few variables, the so-called factors.
All data were analyzed in 2 consecutive steps: univariate analysis and multivariate analysis.
It is based on statistical multivariate analysis techniques, Principal Components Analysis and Cluster Analysis.
Grouping of the data is further elaborated through a multivariate analysis i.e. principal component analysis.
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