• Corpus ID: 86857170

Joint Maximum Likelihood Estimation for High-dimensional Exploratory Item Response Analysis

@article{Chen2017JointML,
  title={Joint Maximum Likelihood Estimation for High-dimensional Exploratory Item Response Analysis},
  author={Yunxiao Chen and Xiaoou Li and Siliang Zhang},
  journal={arXiv: Methodology},
  year={2017}
}
Multidimensional item response theory is widely used in education and psychology for measuring multiple latent traits. However, exploratory analysis of large-scale item response data with many items, respondents, and latent traits is still a challenge. In this paper, we consider a high-dimensional setting that both the number of items and the number of respondents grow to infinity. A constrained joint maximum likelihood estimator is proposed for estimating both item and person parameters, which… 

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