A further test of sequential-sampling models that account for payoff effects on response bias in perceptual decision tasks

Abstract

Recently, Diederich and Busemeyer (2006) evaluated three hypotheses formulated as particular versions of a sequential-sampling model to account for the effects of payoffs in a perceptual decision task with time constraints. The bound-change hypothesis states that payoffs affect the distance of the starting position of the decision process to each decision bound. The drift-rate-change hypothesis states that payoffs affect the drift rate of the decision process. The two-stage-processing hypothesis assumes two processes, one for processing payoffs and another for processing stimulus information, and that on a given trial, attention switches from one process to the other. The latter hypothesis gave the best account of their data. The present study investigated two questions: (1) Does the experimental setting influence decisions, and consequently affect the fits of the hypotheses? A task was conducted in two experimental settings - either the time limit or the payoff matrix was held constant within a given block of trials, using three different payoff matrices and four different time limits - in order to answer this question. (2) Could it be that participants neglect payoffs on some trials and stimulus information on others? To investigate this idea, a further hypothesis was considered, the mixture-of-processes hypothesis. Like the two-stage-processing hypothesis, it postulates two processes, one for payoffs and another for stimulus information. However, it differs from the previous hypothesis in assuming that on a given trial exactly one of the processes operates, never both. The present design had no effect on choice probability but may have affected choice response times (RTs). Overall, the two-stage-processing hypothesis gave the best account, with respect both to choice probabilities and to observed mean RTs and mean RT patterns within a choice pair. Copyright 2008 Psychonomic Society, Inc.