IRTorch: an Item Response Theory Python package

• Item Response Theory (IRT) is a statistical framework used to model the relationshipbetween latent traits (such as abilities or personality traits) and responses to items meantto assess those traits. In this article, we introduce the IRTorch Python package for fittingand evaluating IRT models. The package utilizes PyTorch for parameter optimizationand GPU support. It supports a diverse range of unidimensional and multidimensionalIRT models, both parametric and semiparametric. IRTorch also emphasizes the arbitrarynature of the latent variable scale, which is implicitly assumed and often ignored in otherIRT software. The package provides a flexible framework to implement custom models,scale transformations, and fitting algorithms. We illustrate some of the package’s featuresthrough several examples, including fitting traditional IRT models, using autoencoders forfitting IRT models, and using the bit scale transformation to give a unit of measurementto the latent trait scale.

Ämnesord

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)

NATURAL SCIENCES  -- Mathematical sciences -- Probability Theory and Statistics (hsv//eng)

Nyckelord

IRT

Python

PyTorch

model estimation

autoencoders

Statistics

statistik

education

pedagogik

Psychology

psykologi

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