The Wiener process is a popular model for the simultaneous occurence of reaction times and responses. In particular, the Ratcliff Diffusion Model has recently garnered significant attention. However, in data sets with many conditions, the large number of parameters leads to estimation problems. With a fully explored example, we show how linear and nonlinear constraints of the RDM's parameters across conditions (or participants) do not merely reduce the number of parameters to be estimated, but also how they can be used to test substantive hypotheses when used in combination with model selection strategies. We use very common statistical modeling techniques to construct a "regression diffusion model". We use this model to investigate the effect of practice on reaction time and accuracy, using a large data set from a practice experiment with 25 sessions (10,000 trials total). Two participants were instructed to emphasize accuracy, the other two to emphasize speed. This instruction is expressed in the diffusion model parameters. |