Identifying Latent Structures in Restricted Latent Class Models
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Publication:4559708
DOI10.1080/01621459.2017.1340889zbMath1402.62347OpenAlexW2716847298MaRDI QIDQ4559708
Publication date: 4 December 2018
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/01621459.2017.1340889
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to social sciences (62P25) Applications of statistics to psychology (62P15)
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Cites Work
- Unnamed Item
- Identifiability of diagnostic classification models
- A general method of empirical Q-matrix validation
- The generalized DINA model framework
- Parameter identifiability in a class of random graph mixture models
- Multidimensional item reponse theory.
- Defining a family of cognitive diagnosis models using log-linear models with latent variables
- Identifiability of parameters in latent structure models with many observed variables
- Cluster analysis for cognitive diagnosis: theory and applications
- Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics
- Nonparametric estimation of component distributions in a multivariate mixture
- An application of classical invariant theory to identifiability in nonparametric mixtures.
- Identifiability of restricted latent class models with binary responses
- Estimating multiple classification latent class models
- Higher-order latent trait models for cognitive diagnosis
- Theory of self-learning \(Q\)-matrix
- Describing disability through individual-level mixture models for multivariate binary data
- Extended Bayesian information criteria for model selection with large model spaces
- Data Analytic Methods for Latent Partially Ordered Classification Models
- Nonparametric inference in multivariate mixtures
- Non-uniqueness in probabilistic numerical identification of bacteria
- Partial identification of finite mixtures in econometric models
- The <scp>DINA</scp> model as a constrained general diagnostic model: Two variants of a model equivalency
- On initial item selection in cognitive diagnostic computerized adaptive testing
- Exploratory latent structure analysis using both identifiable and unidentifiable models
- Likelihood-Based Selection and Sharp Parameter Estimation
- Model selection procedure for high‐dimensional data
- Statistical Analysis ofQ-Matrix Based Diagnostic Classification Models
- Tuning Parameter Selection in High Dimensional Penalized Likelihood
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