A Poisson Race Model for the Analysis of the Implicit Association Test

The article presents a Poisson race model for the analysis of the Implicit Association Test (IAT). Four independent and parallel Poisson processes are assumed, one for each category of the IAT. Information about specific characteristics of the stimuli accumulates on the counter of each process until a termination criterion is reached and a response is given. Model parameters are the rates of information accumulation, and the amount of information that is needed before a response is given. The model accounts for both reaction time and response accuracy. The former is determined by the time at which a process wins. The latter depends on the winning process, the category of the presented stimulus, and the kind of block. An empirical application on a Conscientiousness-IAT shows the potential usefulness of the model for understanding the meaning of the implicit measure.