Re: Reducing large datasets
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Again, I was hoping that some of the talented PATN users out there would come out of the woodwork and offer some of their experiences. I am certainly not the font of wisdom, just another view.
OK, on this size dataset non-hierarchical clustering is appropriate. Reducing the complexity by classification is what PATN is about (among other things). Run the classification, label the groups by looking at the box and whisker and then focus in on groups of interest by eliminating the objects in other groups in teh Data Table (first save the analysis though!). See other postings I did yesterday on this.
Depending on the size of the dataset, run non-hierarchical or hierarchical (as the latter will give substructure), ordinate and then analyze the results. The ordination plot is the result to aim at with PATN V3 as there is so much that you can do to help to understand your data with this display-base.
There is not any really good literature I can point you at sad to say. This advice that I seem to offer regulalry is forcing me to consider writing a book myself.
Hope that helps,