Related Experiment Video
Updated: May 16, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
Hierarchical modeling of contingency-based source monitoring: a test of the probability-matching account
Nina R Arnold1, Ute J Bayen, Beatrice G Kuhlmann
1Mathematical and Cognitive Psychology, Institute of Experimental Psychology, Heinrich-Heine-Universität Düsseldorf, Universitätsstr. 1, Geb. 23.02, 40225 Düsseldorf, Germany. nina.arnold@hhu.de
Abstract:
According to the probability-matching account of source guessing (Spaniol & Bayen, Journal of Experimental Psychology: Learning, Memory, and Cognition 28:631-651, 2002), when people do not remember the source of an item in a source-monitoring task, they match the source-guessing probabilities to the perceived contingencies between sources and item types. In a source-monitoring experiment, half of the items presented by each of two sources were consistent with schematic expectations about this source, whereas the other half of the items were consistent with schematic expectations about the other source. Participants' source schemas were activated either at the time of encoding or just before the source-monitoring test. After test, the participants judged the contingency of the item type and source. Individual parameter estimates of source guessing were obtained via beta-multinomial processing tree modeling (beta-MPT; Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010). We found a significant correlation between the perceived contingency and source guessing, as well as a correlation between the deviation of the guessing bias from the true contingency and source memory when participants did not receive the schema information until retrieval. These findings support the probability-matching account.
Related Concept Videos
Theory of Attribution I: Correspondent Inference Theory
Contingency Table
Theory of Attribution II: Kelley's Covariation Theory
Mechanistic Models: Compartment Models in Individual and Population Analysis
McNemar's Test
Determination of Expected Frequency
