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Updated: Jun 23, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Published on: June 3, 2013
Recognition ROCs are curvilinear-or are they? On premature arguments against the two-high-threshold model of
1Department of Psychology, University of Bonn, and Max Planck Institute for Research on Collective Goods, Bonn, Germany. broeder@uni-bonn.de
Abstract:
Recent reviews of recognition receiver operating characteristics (ROCs) claim that their curvilinear shape rules out threshold models of recognition. However, the shape of ROCs based on confidence ratings is not diagnostic to refute threshold models, whereas ROCs based on experimental bias manipulations are. Also, fitting predicted frequencies to actual data is a more sensitive method for model comparisons than ROC regressions. In a reanalysis of 59 published data sets, the 2-high-threshold model (2HTM) fit the data better than an unequal variance signal detection model in about half of the cases. Three recognition experiments with experimental bias manipulation were conducted that yielded linear ROCs and a better fit of the 2HTM in all cases. On the basis of actual data and a simulation, the authors argue that both models are at least equally valid as measurement tools and can perhaps be integrated theoretically.
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