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Auteur : G. David Garson
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Langue : Français, Anglais

A graduate-level introduction to correspondence analysis, which is a method of factoring categorical variables and displaying them in a property space which maps their association in two or more dimensions. Correspondence analysis is a special case of canonical correlation, where one set of entities (category levels rather than variables as in conventional canonical correlation) is related to another set. Table of ContentsOverview5Key Concepts and Terms6Correspondence analysis6Correspondence table6Points6Point distance6Correspondence map6The SPSS correspondence analysis interface8The main correspondence analysis dialog8The model dialog8Dimensions in the solution9Distance measure9Standardization method10Normalization method10The statistics dialog14The plots dialog14SPSS correspondence analysis output15Example15The summary of dimensions table16The correspondence table18The perceptual map18Row points and column points scatterplots20Row profiles and column profiles tables20Contribution tables21Row and column confidence points tables23Line Plots24The permuted correspondence table25Assumptions26Data level and distribution26Data do not need to be detrended26Correlated variables which meet assumptions26Model specification and significance testing27Homogeneity of categories27Correct labeling of dimensions27Numerous categories27Non-negative values28Frequently Asked Questions28What procedures are related to correspondence analysis?28How does correspondence analysis of three variables work in multiple correspondence analysis (MCA)?29Explain active vs. constrained categories.29Explain supplementary categories.31How is the distance between points computed in correspondence analysis?32What is detrended correspondence analysis (DCA)?33Bibliography35Pagecount: 37

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