Parameter estimation approaches for multinomial processing tree models: a comparison for models of memory and judgment

DOI10.1016/J.JMP.2020.102402zbMath1455.91201OpenAlexW3036766126MaRDI QIDQ826887

Thorsten Pachur, Julia Groß

Publication date: 6 January 2021

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

Full work available at URL: https://doi.org/10.1016/j.jmp.2020.102402

zbMATH Keywords

simulationparameter recoveryhindsight biasmultinomial processing tree modelssource memory

Mathematics Subject Classification ID

Cognitive psychology (91E10) Measurement and performance in psychology (91E45)

Uses Software

• MPTinR
• Multitree
• TreeBUGS

Cites Work

• Cognitive model decomposition of the BART: assessment and application
• Hierarchical multinomial processing tree models: a latent-trait approach
• Beta-MPT: multinomial processing tree models for addressing individual differences
• Advances in prospect theory: cumulative representation of uncertainty
• The statistical analysis of general processing tree models with the EM algorithm
• Hierarchical multinomial processing tree models: a latent-class approach
• Bayesian estimation of multinomial processing tree models with heterogeneity in participants and items
• Pooling data versus averaging model fits for some prototypical multinomial processing tree models
• The statistical analysis of a model for storage and retrieval processes in human memory

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