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Two subjects identified a set of perceptually confusable stimuli varying along two continuous, separable dimensions. The data were analyzed using various restricted versions ofthe similarity choice model (Luce, 1963; Shepard, 1957). In the main version, the multidimensional scaling ap- proach to modeling similarity was applied and yielded excellent quantitative accounts of the iden- tification data. A surprising result was that the Euclidean metric provided a far better descrip- tion of psychological distance relationships than the city-block metric, a finding that contrasts with virtually all previous conclusions regarding the appropriate Minkowski r-metric for separable- dimension stimuli. Possible reasons for the discrepancy between the present findings and previ- ous conclusions are considered in the General Discussion section, with Shepard's (1964) seminal study examined in depth. In an initial theoretical section, it is also shown that, for factorial stimu- lus sets, a choice model in which subjects identify values along each component dimension in- dependently is a special case of the full choice model in which overall similarity relationships among stimulus wholes determine identification performance.

Overall similarity and the identification of separable-dimension stimuli: A choice model analysis