Annual Meeting of the Society for Mathematical Psychology, Wisconsin, United States Of America, 21 - 23 July 2018
The speed-accuracy trade-off (SAT), defined as a tendency to trade response time for accuracy and vice versa, is a common problem in two-choice decision tasks. Employing a response deadline procedure provides a full time-course function which describes how cognitive processing unfolds over time. The response deadline procedure allows unbiased estimates of accuracy and speed independent from each other by signalling participants to respond in a controlled condition. In this investigation, a Bayesian model is proposed to estimate the accuracy and speed parameters of SAT functions obtained from the response deadline procedure. The proposed model is derived from a Bayesian signal detection framework and defines accuracy as an exponential growth function of total processing time. The proposed model was applied to both probability matching and item-recognition data sets, and the obtained parameter estimates were evaluated for validity. The findings suggest that the proposed Bayesian framework can provide an effective approach to model SAT curves.