Exploratory restricted latent class models with monotonicity requirements under Pòlya-gamma data augmentation

DOI10.1007/s11336-021-09815-9zbMath1496.62200OpenAlexW4205391587MaRDI QIDQ2088917

James Joseph Balamuta, Steven Andrew Culpepper

Publication date: 6 October 2022

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-021-09815-9

zbMATH Keywords

Bayesianrestricted latent class modelsPòlya-gamma data augmentation

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Related Items (2)

Extending exploratory diagnostic classification models: Inferring the effect of covariates ⋮ A sequential exploratory diagnostic model using a Pólya‐gamma data augmentation strategy

Uses Software

• R
• Armadillo
• Rcpp
• RcppArmadillo

Cites Work

• The generalized DINA model framework
• Inferring the number of attributes for the exploratory DINA model
• Defining a family of cognitive diagnosis models using log-linear models with latent variables
• Cluster analysis for cognitive diagnosis: theory and applications
• RcppArmadillo: accelerating R with high-performance C++ linear algebra
• Bayesian estimation of the DINA \(Q\) matrix
• Identifiability of restricted latent class models with binary responses
• An exploratory diagnostic model for ordinal responses with binary attributes: identifiability and estimation
• A sparse latent class model for cognitive diagnosis
• Partial identifiability of restricted latent class models
• Higher-order latent trait models for cognitive diagnosis
• On the identifiability of diagnostic classification models
• Estimating the cognitive diagnosis \(Q\) matrix with expert knowledge: application to the fraction-subtraction dataset
• Gibbs samplers for logistic item response models via the Pólya-gamma distribution: a computationally efficient data-augmentation strategy
• Identifying Latent Structures in Restricted Latent Class Models
• Sufficient and Necessary Conditions for the Identifiability of the $Q$-matrix
• Statistical Analysis ofQ-Matrix Based Diagnostic Classification Models
• Seamless R and C++ Integration with Rcpp
• Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables
• Extending R with C++: A Brief Introduction to Rcpp

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