Summary
Dual scaling quantifies such categorical data as contingency tables, multiple-choice data, sorting data, paired comparison data, rank-order data, and successive categories data. These data can be classified into two types, incidence data and dominance data. The present study is an overview of some key formulas and several conceptual problems, which require further investigations. Most of them are peculiar to data types, and some remedial procedures are suggested for them as interim measures. Awareness of these difficulties in dual scaling and other related methods seems to be the most notable recent development.
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This study was supported by a grant from the Natural Sciences and Engineering Research Council of Canada to S. Nishisato.
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© 1996 Springer-Verlag Berlin · Heidelberg
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Nishisato, S. (1996). An Overview and Recent Developments in Dual Scaling. In: Gaul, W., Pfeifer, D. (eds) From Data to Knowledge. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79999-0_6
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DOI: https://doi.org/10.1007/978-3-642-79999-0_6
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