Multidimensional scaling ordination

Non-parametric statistical analysis (Bray-Curtis cluster analysis and multidimensional scaling ordination (MDS)) was performed on the GC-MS output to ascertain if any differences could be detected between the animals. MDS has been shown to be a useful technique for analysing chromatographic data, which can be difficult to analyse statistically (see Hayes et al., 2002, 2003). Each point in the MDS plot represents an individual lemur and points that are close together (clumped) correspond to... 

Relationships between the individual LOE can be examined via principal components analysis (PCA). Correlations among principal components for individual LOE indicate concordance or agreement. Relationships between different SQT LOE can also be assessed using other methods including Mantel s test (Legendre and Fortin, 1989) coupled with a measure of similarity or ordination canonical discriminant (or correspondence) analyses multidimensional scaling (MDS). 

Ordinal multidimensional scaling is an empirical technique for iteratively improving a low-dimensional representation of a high-dimensional dataset [53, 70]. The technique is non-parametric, because it is based on the ranks of the dissimilarities rather than their actual values. The iterative procedure aims to minimize a quantity called stress . Small values of stress are obtained if the ranks of the Euclidian distances between points on the low-dimensional plot are similar to the ranks of the dissimilarities of the corresponding observations in the original multidimensional space. 

Fig. 4.16. Result of application of ordinal multidimensional scaling to principal component scat-terplot of Figure 4.12 a. The axes are arbitrary...

Figure 36.4 Two dimensional ordination plots of the selected OGUs on the principal axes of nonmetric multidimensional scaling. Stress value 0.1 I. Minimum spanning trees and bond links are superimposed on the plot the heavier the line the stronger the link. Continuous lines represent strong connections (bond >2), whereas dashed lines loose intergroups relationships.

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