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"Requiring no prior knowledge of correspondence analysis, this text provides anontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte Le Roux and Henry Rouanet, present the material in a practical manner, keeping the needs of researchers foremost in mind." "This supplementary text isappropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as forindividual researchers." --Book Jacket.
"Requiring no prior knowledge of correspondence analysis, this text provides anontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in
Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930–
As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets
Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too adva
Visualization and Verbalization of Data shows how correspondence analysis and related techniques enable the display of data in graphical form, which results in
