Skip to main content
. Author manuscript; available in PMC: 2020 Jan 24.
Published in final edited form as: J Neurosci Methods. 2019 Oct 3;328:108432. doi: 10.1016/j.jneumeth.2019.108432

Fig. 7.

Fig. 7.

Quantile probability (QP) plots showing correct RTs (blue) and error RTs (orange) for two hypothetical observers (case study 1), along with the model predictions (gray dots). Predictions from the four best-fitting models are shown along with the simplest model the DDM. The best fitting models DDMSvSt, DDMSt, DDMSvSzSt, cfkDDMSvSt, and dDDMSvSt are shown. Numbers at the top of each plot show the log likelihood, AIC, and BIC for the model under consideration. AIC and BIC are computed with respect to the DDM. Higher values of log-likelihood are better. When assuming the DDM as the base (reference) model and AIC as the penalized model selection metric, the model DDMSvSt provides the best account of the data. When using BIC as the penalized model selection metric, the model DDMSt provides a better description of the data. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)