Papers › py-irt: A Scalable Item Response Theory Library for Python

py-irt: A Scalable Item Response Theory Library for Python

2 Mar 2022arXiv:2203.01282archive 2025-07-28

John P. Lalor, Pedro Rodriguez

py-irt is a Python library for fitting Bayesian Item Response Theory (IRT) models. py-irt estimates latent traits of subjects and items, making it appropriate for use in IRT tasks as well as ideal-point models. py-irt is built on top of the Pyro and PyTorch frameworks and uses GPU-accelerated training to scale to large data sets. Code, documentation, and examples can be found at https://github.com/nd-ball/py-irt. py-irt can be installed from the GitHub page or the Python Package Index (PyPI).

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