A crossed random effects diffusion model for speeded semantic categorization decisions

Choice reaction times (RTs) are often used as a proxy measure of typicality in semantic categorization studies. However, other item properties have been linked to choice RTs as well. We apply a tailored process model of choice RT to a speeded semantic categorization task in order to deconfound different sources of variability in RT. Our model is based on a diffusion model of choice RT, extended to include crossed random effects (of items and participants). This model retains the interesting process interpretation of the diffusion model’s parameters, but it can be applied to choice RTs even in the case where there are few or no repeated measurements of each participant–item combination. Different aspects of the response process are then linked to different types of item properties. A typicality measure turns out to predict the rate of information uptake, while a lexicographic measure predicts the stimulus encoding time. Accessibility measures cannot reliably predict any component of the decision process

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