Problems when fixing the response bias parameter z in drift diffusion analysis A Commentary on Stafford et al. (2020)

In a simulation study, Stafford et al. (Behavior Research Methods, 52, 2142-2155, 2020) explored the effect of sample size on detecting group differences in ability in the presence of speed-accuracy trade-offs using the Drift Diffusion Model (DDM) and introduced an online tool to perform a power analysis. They found that the DDM approach was superior to analyzing the observed response times and response accuracies alone. In their simulation, they applied the EZ method to estimate the model parameters. In this article, we demonstrate that the EZ method, which cannot estimate the response bias parameter of the DDM, causes severe estimation bias for all parameters if the true response bias is not 0.5. Moreover, the bias patterns differ between EZ and the equivalent maximum likelihood estimation with z fixed at 0.5. This should be taken into consideration when using the otherwise excellent power analysis tool for experimental designs, in which z not equal 0.5 cannot be ruled out or even stipulate it.

Automated summary

This article discusses the impact of sample size on detecting group differences in ability and introduces an online tool for power analysis through a simulation study. The results show that the approach using the Drift Diffusion Model is superior to analyzing response times and accuracies separately. However, the article also highlights the estimation bias issue with the EZ method.