Check out the preprint of our new paper on the importance of including response time data in the analysis and comparison of dynamic models of context effects. Using state-of-the-art response time modeling and data from 12 different experiments appearing in 6 different published studies, we compared four previously proposed models of context effects: Multi-alternative Decision Field Theory (MDFT), the Leaky-Competing Accumulator (LCA), the Multi-attribute Linear Ballistic Accumulator (MLBA), and the Associative Accumulation Model (AAM). Our results show that response time data is critical at distinguishing among these models and that using choice data alone can lead to inconclusive results for some datasets. The paper will appear in Psychonomic Bulletin & Review.
Computational Decision Making Lab 