There is a revised version at: https://osf.io/4nx2vPrevious work (Glautier, 2013) showed that the responses made by humans on trial n insimple associative learning tasks were influenced by events that took place on trial n−1and a simple extension of the Rescorla-Wagner Model (RWM Rescorla & Wagner,1972), the Memory Environment Cue Array (MECA) model, was presented to accountfor those results. In the current work further evidence of non-local influences onresponding during associative learning

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... sks is presented. The Rescorla-Wagner modeland the MECA model are evaluated as models for the observed data using qualitative,näive maximum likelihood, and Akaike weight analyses. In two experiments the Akaikeweight analyses strongly supported the simpler Rescorla-Wagner model over the MECAmodel but the qualitive and näive maximum likelihood analyses strongly supported theMECA model model over the simpler Rescorla-Wagner model. In Experiment 2 thisapparent conflict was resolved using a generalisation criterion test (Ahn, Busemeyer,Wagenmakers, & Stout, 2008; Busemeyer & Wang, 2000) which gave clear support tothe MECA model over the Rescorla-Wagner model. These results demonstrate thesuperiority of model selection using predictive validity, where possible, over selectionusing statistical adjustments for model complexity. Data and code available at Glautier(2017).