It is difficult to estimate and examine correlations between individual preferences for alternatives using the present Scheffé-type paired comparison models. In this paper, we propose two models that address individual preferences for alternatives. One is a simple model that makes it possible to estimate correlations between individual preferences. The other is an improved model that makes it possible to extract independent components from those correlations. Paired comparison data were collected in a survey about preferences for several new product names. Analysis of this data shows that the proposed models enabled the estimation not only of average preferences for alternatives, but also correlations between individual preferences and loading matrices for independent components. The effectiveness of the proposed methods was confirmed by the interpretations of those estimates.
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