Bayesian inference for multidimensional graded response model using Pólya-Gamma latent variables

DOI10.1080/00949655.2023.2212313MaRDI QIDQ6141455

Zhihui Fu, Unnamed Author

Publication date: 23 January 2024

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

zbMATH Keywords

Gibbs samplingdata augmentationmultidimensional graded response modelPólya-Gamma distribution

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Statistics (62-XX)

Cites Work

• Unnamed Item
• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• Item response theory for longitudinal data: population parameter estimation
• Geometric ergodicity of Pólya-Gamma Gibbs sampler for Bayesian logistic regression with a flat prior
• Inference from iterative simulation using multiple sequences
• Item response theory in AI: analysing machine learning classifiers at the instance level
• MCMC estimation and some model-fit analysis of multidimensional IRT models
• Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
• Bayesian Measures of Model Complexity and Fit
• Sensitivity analysis and choosing between alternative polytomous IRT models using Bayesian model comparison criteria
• Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables

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