Abstract
Dual scaling and correspondence analysis are closely related, mathematically equivalent, data analysis methods; see, for example, Tenenhaus and Young (1984), Greenacre (1984). Typically, the data one subjects to either correspondence analysis or dual scaling are in the format of a so-called contingency matrix, i.e. a matrix consisting of frequencies of co-occurrences. There exist however modifications of the methods that make it possible to analyse also other types of data. One of these modifications involves the treatment of preference data. Both Greenacre (1984, 1993) and Nishisato (1980, 1994) treat the analysis of such data, however, partly due to differences in the format and exact nature of the data, the methods they propose appear to be different. Because of this it would be, as Greenacre pointed out in his (1996) book review, “interesting to compare the two approaches more closely”.
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van de Velden, M. (2000). Dual Scaling and Correspondence Analysis of Rank Order Data. In: Heijmans, R.D.H., Pollock, D.S.G., Satorra, A. (eds) Innovations in Multivariate Statistical Analysis. Advanced Studies in Theoretical and Applied Econometrics, vol 36. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4603-0_6
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DOI: https://doi.org/10.1007/978-1-4615-4603-0_6
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