Hierarchical single- and dual-process models of recognition memory

DOI10.1016/j.jmp.2010.08.007zbMath1208.91126OpenAlexW2063314770MaRDI QIDQ631937

Michael S. Pratte, Jeffrey N. Rouder

Publication date: 14 March 2011

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmp.2010.08.007

zbMATH Keywords

signal detectionBayesianhierarchical modelsrecognition memorydual process

Mathematics Subject Classification ID

Cognitive psychology (91E10) Memory and learning in psychology (91E40) Applications of statistics to psychology (62P15)

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Uses Software

• BayesDA

Cites Work

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• Understanding memory impairment with memory models and hierarchical Bayesian analysis
• A statistical model for discriminating between subliminal and near-liminal performance
• A truncated probit item response model for estimating psychophysical thresholds
• Assessing model mimicry using the parametric bootstrap.
• Signal detection models with random participant and item effects
• Problematic effects of aggregation in \(z\)ROC analysis and a hierarchical modeling solution
• Bayesian residual analysis for binary response regression models
• Bayesian Measures of Model Complexity and Fit
• Bayes Factors