Corpus ID: 219176993

A Nonparametric Bayesian Item Response Modeling Approach for Clustering Items and Individuals Simultaneously

@article{Hu2020ANB,
  title={A Nonparametric Bayesian Item Response Modeling Approach for Clustering Items and Individuals Simultaneously},
  author={Guanyu Hu and Zhihua Ma and Insu Paek},
  journal={arXiv: Applications},
  year={2020}
}
Item response theory (IRT) is a popular modeling paradigm for measuring subject latent traits and item properties according to discrete responses in tests or questionnaires. There are very limited discussions on heterogeneity pattern detection for both items and individuals. In this paper, we introduce a nonparametric Bayesian approach for clustering items and individuals simultaneously under the Rasch model. Specifically, our proposed method is based on the mixture of finite mixtures (MFM… 

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