Modeling within-item dependencies in parallel data on test responses and brain activation

DOI10.1007/s11336-020-09741-2zbMath1476.62246OpenAlexW3122113615WikidataQ114222782 ScholiaQ114222782MaRDI QIDQ823875

Xiangrui Li, Zhong-Lin Lu, Minjeong Jeon, Jevan Luo, Paul De Boeck

Publication date: 16 December 2021

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-020-09741-2

zbMATH Keywords

theory of mindparallel datajoint analysisconditional dependencyfMRI activationsresponse accuracy

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Cites Work

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• Two simple examples for understanding posterior \(p\)-values whose distributions are far from unform
• Response mixture modeling: accounting for heterogeneity in item characteristics across response times
• Statistical tests of conditional independence between responses and/or response times on test items
• RT-MPTs: process models for response-time distributions based on multinomial processing trees with applications to recognition memory
• Modelling conditional dependence between response time and accuracy
• Generalized latent trait models
• Generalized multilevel structural equation modeling
• Generalized processing tree models: jointly modeling discrete and continuous variables
• A hierarchical framework for modeling speed and accuracy on test items
• Spontaneous and imposed speed of cognitive test responses
• Bayesian Measures of Model Complexity and Fit

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