How framing statistical statements affects subjective veracity: Validation and application of a multinomial model for judgments of truth

33Citations
Citations of this article
60Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Extending the well-established negativity bias in human cognition to truth judgments, it was recently shown that negatively framed statistical statements are more likely to be considered true than formally equivalent statements framed positively. However, the underlying processes responsible for this effect are insufficiently understood. Therefore, a multinomial processing tree model is herein proposed to distinguish between differences in (a) knowledge or (b) response bias that may account for the framing effect. Three model validation experiments supported the psychological interpretability of model parameters. Model application revealed that the framing effect can be considered a bias: Given insufficient knowledge, individuals more likely guessed " true" when faced with a negatively framed statistical statement. The probability of conclusive knowledge, however, remained constant across frames. In summary, this article puts forwards and validates a formal model that can be used more generally to investigate processes underlying truth judgments. Based on this model, it is herein shown that one particular phenomenon - framing effects observed for statistical statements - can be considered a response bias, rather than the upshot of differential knowledge. © 2012 Elsevier B.V.

Cite

CITATION STYLE

APA

Hilbig, B. E. (2012). How framing statistical statements affects subjective veracity: Validation and application of a multinomial model for judgments of truth. Cognition, 125(1), 37–48. https://doi.org/10.1016/j.cognition.2012.06.009

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free