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Response time (RT) data play an important role in psychology. The diffusion model (DM) allows to analyze RT-data in a two-alternative-force-choice paradigm using a particle drift diffusion modeling approach. It accounts for right-skewed distributions in a natural way. However, the model incorporates seven parameters, the roles of which are difficult to comprehend from the model equation. Therefore, the present article introduces the diffusion model visualizer (DMV) allowing for interactive manipulation of each parameter and plotting the resulting RT densities. Thus, the DMV serves as a valuable tool for understanding the specific role of each model parameter. It may come in handy for didactical purposes and in research context. It allows for tracking down parameter estimation problems by delivering the model-based ideal densities, which can be juxtaposed to the data-based densities. It will also serve a valuable purpose in detecting outliers. The article describes the basics of the DM along with technical details of the DMV and gives several hints for its usage.
Rainer W. Alexandrowicz (Thu,) studied this question.