Abstract
In source-monitoring experiments, participants study items from two sources (A and B). At test, they are presented Source A items, Source B items, and new items. They are asked to decide whether a test item is old or new (item memory) and whether it is a Source A or a Source B item (source memory). Hautus, Macmillan, and Rotello (2008) developed models, couched in a bivariate signal detection framework, that account for item and source memory across several data sets collected in a confidence-rating response format. The present article enlarges the set of candidate models with a discrete-state model. The model is a straightforward extension of Bayen, Murnane, and Erdfelder's (1996) multinomial model of source discrimination to confidence ratings. On the basis of the evaluation criteria adopted by Hautus et al., it provides a better account of the data than do Hautus et al.'s models.
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The research reported in this article was supported by Grant Kl 614/31-1 from the Deutsche Forschungsgemeinschaft to the first author and by Grant SFRH/BD/48346/2008 from the Fundação para a Ciência e Tecnologia to the second author.
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Klauer, K.C., Kellen, D. Toward a complete decision model of item and source recognition: A discrete-state approach. Psychonomic Bulletin & Review 17, 465–478 (2010). https://doi.org/10.3758/PBR.17.4.465
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DOI: https://doi.org/10.3758/PBR.17.4.465