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Blocked Indicator Species Analysis
Dufrêne and Legendre’s (1997) method for Indicator Species Analysis can be adapted to a randomized block experiment or a paired-sample design. The data are pre-relativized by species within blocks (or pairs), such that the sum across groups equals one for each block. If a species is absent from a block, the abundances are maintained at zero. The relativization alters the relative abundance portion of the Indicator Value (IV) index to focus on within block differences. Then the ISA is run as usual. The randomization test differs from regular ISA in that instead of an unconstrained permutation of group identifiers, groups are randomly permuted within blocks.
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New Matrix Format
Categorical values can now be either numerical or text with a maximum of 20 characters
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Because the hilltops are based on a contoured response surface, you can better understand the basis for hilltop plots by reading about contour overlays. The chief difference in use between the hilltops and the contour plots is that contour plots can be shown for only one variable at a time, while one can graph many hilltops on the same ordination. This comes at a loss of information in that most of the contour plot is discarded when converting to a hilltop, but has the advantage of representing multiple nonlinear relationships at once..
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The objective of my courses is the understanding of the process of multivariate data analysis and not so much on the technical part, even the latter results in a more thorough understanding of the procedures applied. When students understand why and how to effectively do multivariate statistical analyses of their data, they can then use, with little effort, other programs or packages as well.
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