Pages that link to "Item:Q6160317"
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The following pages link to Learning latent and hierarchical structures in cognitive diagnosis models (Q6160317):
Displaying 13 items.
- Using penalized EM algorithm to infer learning trajectories in latent transition CDM (Q823864) (← links)
- Defining a family of cognitive diagnosis models using log-linear models with latent variables (Q1029512) (← links)
- Regularized latent class analysis with application in cognitive diagnosis (Q1682442) (← links)
- A sparse latent class model for cognitive diagnosis (Q2195815) (← links)
- Attribute hierarchy models in cognitive diagnosis: identifiability of the latent attribute space and conditions for completeness of the Q-matrix (Q2304089) (← links)
- Hierarchical diagnostic classification models: a family of models for estimating and testing attribute hierarchies (Q2452304) (← links)
- \(Q\)-matrix theory based on attribute implications (Q2990517) (← links)
- A general proof of consistency of heuristic classification for cognitive diagnosis models (Q4614702) (← links)
- Cognitive diagnosis models for multiple strategies (Q5234439) (← links)
- Identifiability of hidden Markov models for learning trajectories in cognitive diagnosis (Q6175678) (← links)
- A tensor-EM method for large-scale latent class analysis with binary responses (Q6175692) (← links)
- Bayesian inference for an unknown number of attributes in restricted latent class models (Q6175693) (← links)
- Latent conjunctive Bayesian network: unify attribute hierarchy and Bayesian network for cognitive diagnosis (Q6616336) (← links)
