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. 2018 Jul;125(4):512–544. doi: 10.1037/rev0000102

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© 2018 The Author(s)

This article has been published under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s). Author(s) grant(s) the American Psychological Association the exclusive right to publish the article and identify itself as the original publisher.

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Decision probability as a function of the number of attribute values sampled from long-term memory. Each panel summarizes mean-average decision probability of 5,000 simulations for each number of samples. With the number of samples from long-term memory, the attraction (left panel), compromise (middle panel), and similarity (right panel) effects all become weaker. In this illustration, attribute values in long-term memory are assumed to follow normal distribution whose mean is the attribute values of Car A, and standard deviation is the absolute difference between Cars A and B. We also assumed that attribute values in long-term memory are weakly correlated at Pearson coefficient = −.2. However, the findings of weakened effects with more long-term memory samples are robust across many possible distributions.