| Abstract: | The article presents the feature sampling signal detection (FS-SDT) model, an extension of the multivariate signal detection (SDT) model. The FS-SDT model assumes that, because of attentional shifts, different subsets of features are sampled for different presentations of the same multidimensional stimulus. Contrary to the SDT model, the FS-SDT model enables the estimation of pure perceptual effects that are uncontaminated by strategic attention shifts. The consideration of feature sampling in detection and identification opens a new perspective on the problem of measuring, respectively, the separability and integrality of stimulus dimensions. Disregarding feature sampling as a component process in detection and identification usually results in biased estimations of perceptual independence concepts relevant for judgments of whether stimulus dimensions are processed independently. (PsycINFO Database Record (c) 2010 APA, all rights reserved) |
