A comparison of correlation and regression approaches for multinomial processing tree models

DOI10.1016/j.jmp.2020.102400zbMath1455.91203OpenAlexW3033474943MaRDI QIDQ826884

Lisa J. Jobst, Daniel W. Heck, Morten Moshagen

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.2020.102400

zbMATH Keywords

individual differencesmultinomial modelinghierarchical Bayesian modelingcorrection for attenuationparameter correlations

Mathematics Subject Classification ID

Memory and learning in psychology (91E40) Measurement and performance in psychology (91E45)

Related Items (1)

Cognitive psychometrics: the scientific legacy of William H. Batchelder (1940--2018)

Uses Software

• R
• MASS (R)
• JAGS
• runjags
• MPTinR
• Multitree
• TreeBUGS
• RRreg

Cites Work

• Hierarchical multinomial processing tree models: a latent-trait approach
• Beta-MPT: multinomial processing tree models for addressing individual differences
• The theory of test validity and correlated errors of measurement
• Inference from iterative simulation using multiple sequences
• 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
• Statistical Analysis of Financial Data in S-Plus

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