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ERIC Number: EJ878837
Record Type: Journal
Publication Date: 2010-Mar
Pages: 29
Abstractor: As Provided
Reference Count: N/A
ISBN: N/A
ISSN: ISSN-0033-3123
Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach
Klauer, Karl Christoph
Psychometrika, v75 n1 p70-98 Mar 2010
Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into account and to assess parameter correlations. The model is estimated using Bayesian methods with weakly informative hyperprior distribution and a Gibbs sampler based on two steps of data augmentation. Estimation, model checks, and hypotheses tests are discussed. The new method is illustrated using a real data set, and its performance is evaluated in a simulation study.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A