An unfolding model is proposed for analyzing the confusion matrices obtained from stimulus identification experiments. In the model, row and column stimuli in the matrices are represented as two sets of points in a multidimensional space, and confusion probabilities are expressed as a function of the distances between the row and the column points. The coordinates of the points are estimated by the maximum likelihood method under a constraint. The proposed model enables us to explore interesting aspects of the perceptual representations of the stimuli, as illustrated by two examples. Some advantages of the proposed model are discussed in regard to its psychological implication.
Choice Behavior Confusion