Exploring Multidimensional Quantification Space
Dual scaling deals with two distinct types of categorical data, incidence data and dominance data. While perfect row-column association of an incidence data matrix does not mean that the data matrix can be fully explained by one solution, dominance data with perfect association can be explained by one solution. Considering a main role of quantification theory is to explain data in multidimensional space, the present study presents a non-technical look at some fundamental aspects of quantification space that are used for analysis of the two types of data.
KeywordsPrincipal Component Analysis Incidence Data Multiple Correspondence Analysis Principal Component Analysis Result Quantification Space
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