A Two-Step Signal Detection Model of Belief Bias

Abstract

When asked to assess the deductive validity of an argument, people are influenced by their prior knowledge of the content. Recently, two competing explanations for this belief bias effect have been proposed, each based on signal detection theory. Under a response bias explanation, people set more lenient decision criteria for believable than for unbelievable arguments. Alternatively, believable and unbelievable arguments may differ in subjective argument strength for both valid and invalid items. Two experiments tested these accounts by asking participants to assess the validity of categorical syllogisms and rate their confidence. Conclusion-believability was manipulated either within- or between-groups. A two-step signal detection model was applied to examine the effects on the relative location of the decision threshold and the distributions of argument strength. Equivalent belief bias effects were found when believability was manipulated within- and between-groups, supporting the view that the belief bias effect is due to response bias.


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