What is the airspeed velocity of an unladen swallow? Modeling numerical judgments of realisitc stimuli

Research on processes of multiple-cue judgments usually uses artificial stimuli with predefined cue structures, such as artificial bugs with four binary features like back color, belly color, gland size, and spot shape. One reason is that the cognitive models used in this area need known cues and cue values. This limitation makes it difficult to apply the models to research questions with complex naturalistic stimuli with unknown cue strucuture. In two studies, building on early categorizaton research, we demonstrate how cues and cue values of complex naturalistic stimuli can be extracted from pairwise similarity ratings with a multidimensional scaling analysis and then be used in a state-of-the art hierarchical Bayesian model of numerical judgments. In the first study, we show that predefined cue structures of artificial stimuli are well recovered by a MDS analysis of similarity judgments and that using these MDS-based attributes as cues in a cognitive model of judgment data from an existing experiment leads to the same inferences as when the original cue values were used. In the second study, we use the same procedure to replicate previous findings from multiple-cue judgment literature using complex naturalistic stimuli.