title: Diffusion models in experimental psychology: a practical introduction.
abstract: Stochastic diffusion models (Ratcliff, 1978) can be used to analyze response time data from binary decision tasks. They provide detailed information about cognitive processes underlying the performance in such tasks. Most importantly, different parameters are estimated from the response time distributions of correct responses and errors that map (1) the speed of information uptake, (2) the amount of information used to make a decision, (3) possible decision biases, and (4) the duration of nondecisional processes. Although this kind of model can be applied to many experimental paradigms and provides much more insight than the analysis of mean response times can, it is still rarely used in cognitive psychology. In the present paper, we provide comprehensive information on the theory of the diffusion model, as well as on practical issues that have to be considered for implementing the model.
authors.affiliation: Psychologisches Institut, Ruprecht-Karls-Universität Heidelberg, <location>Germany</location>
authors.forename: Andreas
authors.initials: A
authors.lastname: Voss
authors.forename: Markus
authors.initials: M
authors.lastname: Nagler
authors.forename: Veronika
authors.initials: V
authors.lastname: Lerche
mesh_terms: D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008960:Models, Psychological; D011589:Psychology, Experimental; D011930:Reaction Time / Q000502:physiology*
keywords: DMAT; EZ diffusion; diffusion model; fast-dm; mathematical model; response times