Understanding memory impairment with memory models and hierarchical Bayesian analysis

DOI10.1016/j.jmp.2010.08.003zbMath1208.91130OpenAlexW2134642857WikidataQ57710674 ScholiaQ57710674MaRDI QIDQ631940

William R. Shankle, James P. Pooley, Michael D. Lee

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.2010.08.003

zbMATH Keywords

Alzheimer's diseasedementiacognitive psychometricshuman memorymeasurement models

Mathematics Subject Classification ID

Medical applications (general) (92C50) Cognitive psychology (91E10) Memory and learning in psychology (91E40)

Related Items

An application of multinomial processing tree models and Bayesian methods to understanding memory impairment, How cognitive modeling can benefit from hierarchical Bayesian models, Hierarchical single- and dual-process models of recognition memory

Uses Software

• WinBUGS
• BayesDA

Cites Work

• Unnamed Item
• Unnamed Item
• Hierarchical single- and dual-process models of recognition memory
• Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task
• Graphical models
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)