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Landscape metrics and nitrogen loading are summarized by equal overland flow-length rings, and their association is examined by using multivariate statistical analysis.
The main aim of this paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques.
This was achieved by using multivariate statistical tools, which identified markers (metabolites and genes) correlating with a particular genotype.
These results were analyzed by using multivariate statistical techniques (principal component analysis (PCA) and cluster analysis (CA)).
By using multivariate statistical analysis we were able to distinguish patient groups and detect specific metabolic and cytokine/chemokine patterns associated with septic shock and its mortality.
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They can be reduced by using multivariate statistics.
Omics-based biomarkers are generated by measuring many more variables and using multivariate statistical models.
The difference in the gut microbiome patterns arising from gene knockout is also readily differentiated using multivariate statistical analysis, as shown by the PCoA plot in Figure S2.
The difference in the gut microbiome patterns arising from arsenic is readily differentiated using multivariate statistical analysis, as shown by the PCoA plot in Figure 1C.
Using multivariate statistical methods, four types were identified.
The method was developed and evaluated through orthogonal experimental design using multivariate statistical analysis.
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by using multivariate statistic
by using multivariate negative
by using multivariate experimental
by using multivariate -adic
by using several statistical
by using multivariate chemometrical
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by developing multivariate statistical
by using multivariate normal
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by using multivariate logistic
by using multivariate data
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