The belief bias effect is aptly named: A reply to Klauer and Kellen (2011).

Abstract

In "Assessing the Belief Bias Effect With ROCs: It's a Response Bias Effect," Dube, Rotello, and Heit (2010) examined the form of receiver operating characteristic (ROC) curves for reasoning and the effects of belief bias on measurement indices that differ in whether they imply a curved or linear ROC function. We concluded that the ROC data are in fact curved and that analyses using statistics that assume a linear ROC are likely to produce Type I errors. Importantly, we showed that the interaction between logic and belief that has inspired much of the theoretical work on belief bias is in fact an error stemming from inappropriate reliance on a contrast (hit rate-false alarm rate) that implies linear ROCs. Dube et al. advanced a new model of belief bias, which, in light of their data, is currently the only plausible account of the effect. Klauer and Kellen (2011) disputed these conclusions, largely on the basis of speculation about the data collection method used by Dube et al. to construct the ROCs. New data and model-based analyses are presented that refute the speculations made by Klauer and Kellen. We also show that new modeling results presented by Klauer and Kellen actually support the conclusions advanced by Dube et al. Together, these data show that the methods used by Dube et al. are valid and that the belief bias effect is simply a response bias effect.