Random Effects Multinomial Processing Tree Models: A Maximum Likelihood Approach

The present article proposes and evaluates marginal maximum likelihood (ML) estimation methods for hierarchical multinomial processing tree (MPT) models with random and fixed effects. We assume that an identifiable MPT model with S parameters holds for each participant. Of these S parameters, R para...

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Detalles Bibliográficos
Autores principales: Nestler, Steffen, Erdfelder, Edgar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Theory and Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444666/
https://www.ncbi.nlm.nih.gov/pubmed/37247167
http://dx.doi.org/10.1007/s11336-023-09921-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444666/
https://www.ncbi.nlm.nih.gov/pubmed/37247167
http://dx.doi.org/10.1007/s11336-023-09921-w

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