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The stochastic difference model assumes that decision makers trade normalized attribute value differences when making choices. The model is stochastic, with choice probabilities depending on the normalized difference variable, d, and a decision threshold, delta. The decision threshold indexes a person's sensitivity to attribute value differences and is a free estimated parameter of the model. Depending on the choice context, a person may be more or less sensitive to attribute value differences, and hence delta may be used to measure context effects. With proportional difference used as the normalization, the proportional difference model (PD) was tested with 9 data sets, including published data (e.g., J. L. Myers, M. M. Suydam, A. Tversky, 1969). The model accounted for individual and group data well and described violations of stochastic dominance, independence, and weak and strong stochastic transitivity.
Claudia González‐Vallejo (Tue,) studied this question.