Aimed at researchers and students interested in non-linear analysis of categorical variables, this book explains multivariate analysis geometrically rather than through the use of formal algebraic formulae. It first covers what the desirable properties of a geometric display should look like on the basis of classical analysis. Next, it discusses how these desirable properties can be enhanced by gradually eliminating the restrictions imposed by an a priori technique. The book goes on to explore such topics as the relation of principal components analysis, canonical analysis and generalized canonical analysis to one another, optimal quantification for one, two and three variables, and how many dimensions are needed for optimal quantifi
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Aimed at researchers and students interested in nonlinear analysis of categorical variables, Multivariate Analysis of Categorical Data: Theory explains multivariate analysis geometrically rather than through the use of formal algebraic formulae. Asterisked sections, however, are included that present an algebraic explanation for readers who are more familiar with classical multivariate analysis. The author first covers what the desirable properties of a geometric display should look like on the basis of classical analysis. Next, he discusses how these desirable properties can be enhanced by gradually eliminating the restrictions imposed by an a priori technique. He then explores such topics as the relation of principal components analysis; canonical analysis and generalized canonical analysis to one another; optimal quantification for one, two, and three variables; and how many dimensions are needed for optimal quantification.
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