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For example, QT est can estimate binary choice probabilities subject to the constraint that the error probabilities, summed over all gamble pairs, are limited to some maximum amount, say 0. 5 (this is a restrictive model allowing at most an average error rate of 5 per gamble pair), and provide a goodness-of-fit for KT-V4. Again, HDM fits perfectly, but DM1 and DM13 reject that model with small p-values.

The bottom panel of the table illustrates a very different class of models and their test. This captures the idea that a decision maker satisfying.