This article compares, via synthetic data analysis, the performance of five different methods for scaling averaged dissimilarities data under conditions involving individual differences in “perception.” All methods perform well when no “degradation” of the (simulated) ratings is entailed. When the data are transformed to zero-one values—a procedure sometimes followed in applied studies—all procedures perform poorly compared to the no-degradation case. Implications of these results for scaling applications involving group solutions are discussed.
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