Linear ballistic accumulator models of confidence and response time
Accurate decisions tend to be both confident and fast. Nonetheless, there are relatively few models that can simultaneously address this three-way relationship, especially for single stage decisions where participants indicate both their choice and their confidence. Extending on a common decision architecture of the linear ballistic accumulator framework, two models have been proposed – 1) a Multiple Threshold Race model which instantiates the Balance-of-Evidence hypothesis where confidence is determined through the difference between accumulated evidence for competing options (e.g., Reynolds, Osth, Kvam, & Heathcote, in revision), and 2) a newly developed Confidence Accumulator model which assumes that confidence itself is accumulated independently for each confidence option. To test these two confidence architectures, we ran two experiments manipulating the length of the confidence rating scale across 2-, 4-, or 6-options in a recognition memory task along with a perceptual task. Different models were compared that made different allowance for how the length of the confidence scale affected model parameters. While both model classes found that thresholds were affected by the length of the scale, drift rates were only minimally affected. Implications for models of confidence and response time will be discussed.
Haomin Chen graduated from the University of Melbourne with a B.A. majoring in Psychology in 2019, and obtained a 1st Class Honours in Psychology in 2020. Haomin is currently a 3rd year PhD student working under the supervision of Dr. Adam Osth in the Melbourne School of Psychological Sciences at the University of Melbourne. Her research is focused on investigating the three-way relationship between confidence, response latency and accuracy using a decision model.