Currently, the XLstat PCA option allows the addition of confidence ellipses, however the MDS option does not. In order to interpret an MDS - not only does the location of the data points for each product/subject matter, but also their 95% confidence ellipses- which tell you which products are different and which are the same (based on the overlap of their confidence ellipses)- with just the data points there can be several products/subjects that one cannot differentiate if they are close enough to be considered similar. The MDS uses the input of a similarity/dissimilarity matrix to obtain a 2-D visualization of the similarities and differences between products/subjects based on their proximity to one another in 2-D space. Would be great to be able to perform these tests using summarized data too (eg: sample means, sample sizes) in case raw data are not available. For example, with MDS, it is possible to reconstitute the position of towns. XLSTAT requires the input of raw data to run parametric tests such as student test, levene's test, etc. p is generally fixed at 2 or 3 so that the objects may be visualized easily.
Similarity matrix how to xlstat series#
MDS is a form of a PCA- often used in sensory science. Multidimensional Scaling ( MDS) is used to go from a proximity matrix ( similarity or dissimilarity) between a series of N objects to the coordinates of these same objects in a p-dimensional space.
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