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Judgment or recall: On the problematic procedure for estimating parameters in exemplar models of quantitative judgment

David Izydorczyk
University of Mannheim ~ Experimental Psychology
Prof. Arndt Bröder

Exemplar models are often used in research on multiple-cue judgments to describe the underlying process of participant’s responses. In these experiments, participants are repeatedly presented with the same exemplars (e.g., poisonous bugs) and instructed to memorize these exemplars and their corresponding criterion values (e.g., the toxicity of a bug). We propose that by using this experimental paradigm the judgments of participants in a multiple-cue judgment experiment are a mixture of two qualitatively distinct cognitive processes: judgment and recall. When participants are presented with one of the trained exemplars in some later block of the experiment, they either have learned the exemplar and its respective criterion value and are thus able to recall the exact value, or they have not learned it and thus have to judge its criterion value, as if it was a new stimulus. However, the analysis procedure and the models usually applied do not differentiate between these processes and the data generated by them. We therefore investigated the effect of disregarding the distinction between these two processes on the parameter recovery and the model fit of one exemplar model. The results of a computer simulation and the reanalysis of five experiments show that the current combination of experimental design and modelling procedure can lead to extremely bias in parameter estimates and thus impaired validity of these parameters, as well as negatively affect the fit and predictive performance of the model. As a remedy, we present a latent-mixture extension of the original model which solves these issues.



multiple-cue judgment
exemplar model

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Cite this as:

Izydorczyk, D., & Bröder, A. (2021, July). Judgment or recall: On the problematic procedure for estimating parameters in exemplar models of quantitative judgment. Paper presented at Virtual MathPsych/ICCM 2021. Via