Analyzing distances
Justin Fenty
MRC Institute for Environment and Health
University of Leicester
[email protected]
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Abstract. Gower and Krzanowski (1999) described the analysis of a multivariate dataset
that violated the assumptions of normality for multivariate analysis of
variance. They developed a method comprising two aspects: a graphical
representation of the points in a fewer number of dimensions, known as
principal coordinate analysis; and a technique similar to MANOVA except that
it was based on partitioning the distances between subjects, rather than
sums of squares, and did not assume that the data followed any particular
distribution. This article summarizes both aspects of their analysis and
describes the Stata pco and aod commands, which perform
principal coordinate analysis and analysis of distance.
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Justin Fenty
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multivariate data, principal coordinate analysis, multidimensional scaling, Euclidean distance, Gower's general coefficient of similarity, eigenvectors, analysis of distance, MANOVA, partitioning of squared distance, randomization tests, contrasts, idempotent matrices
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