Interpreting the parameters of the diffusion model: an empirical validation

Mem Cognit. 2004 Oct;32(7):1206-20. doi: 10.3758/bf03196893.

Abstract

The diffusion model (Ratcliff, 1978) allows for the statistical separation of different components of a speeded binary decision process (decision threshold, bias, information uptake, and motor response). These components are represented by different parameters of the model. Two experiments were conducted to test the interpretational validity of the parameters. Using a color discrimination task, we investigated whether experimental manipulations of specific aspects of the decision process had specific effects on the corresponding parameters in a diffusion model data analysis (see Ratcliff, 2002; Ratcliff & Rouder, 1998; Ratcliff, Thapar, & McKoon, 2001, 2003). In support of the model, we found that (1) decision thresholds were higher when we induced accuracy motivation, (2) drift rates (i.e., information uptake) were lower when stimuli were harder to discriminate, (3) the motor components were increased when a more difficult form of response was required, and (4) the process was biased toward rewarded responses.

MeSH terms

  • Adult
  • Attention
  • Data Interpretation, Statistical
  • Decision Making*
  • Discrimination Learning
  • Female
  • Humans
  • Male
  • Models, Statistical*
  • Motivation
  • Pattern Recognition, Visual
  • Reaction Time*
  • Reproducibility of Results