Representing probabilistic models of knowledge space theory by multinomial processing tree models
- 11 March 2020
- journal article
- research article
- Published by Elsevier BV in Journal of Mathematical Psychology
- Vol. 96, 102329
- https://doi.org/10.1016/j.jmp.2020.102329
Abstract
No abstract availableKeywords
Funding Information
- Deutsche Forschungsgemeinschaft (GRK2277)
This publication has 42 references indexed in Scilit:
- Minimum Discrepancy Estimation in Probabilistic Knowledge StructuresElectronic Notes in Discrete Mathematics, 2013
- Assessing the local identifiability of probabilistic knowledge structuresBehavior Research Methods, 2012
- A Note on the Connection Between Knowledge Structures and Latent Class ModelsMethodology, 2011
- About the Connection Between Knowledge Structures and Latent Class ModelsMethodology, 2005
- Representing parametric order constraints in multi-trial applications of multinomial processing tree modelsJournal of Mathematical Psychology, 2004
- Cognitive psychometrics: Assessing storage and retrieval deficits in special populations with multinomial processing tree models.Psychological Assessment, 2002
- Cognitive psychometrics: Assessing storage and retrieval deficits in special populations with multinomial processing tree models.Psychological Assessment, 2002
- Introduction to knowledge spaces: How to build, test, and search them.Psychological Review, 1990
- Multinomial modeling and the measurement of cognitive processes.Psychological Review, 1988
- Separation of storage and retrieval factors in free recall of clusterable pairs.Psychological Review, 1980