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Using Stan for Item Response Theory Models
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Ames, Allison J.; Au, Chi Hang – Measurement: Interdisciplinary Research and Perspectives, 2018
Stan is a flexible probabilistic programming language providing full Bayesian inference through Hamiltonian Monte Carlo algorithms. The benefits of Hamiltonian Monte Carlo include improved efficiency and faster inference, when compared to other MCMC software implementations. Users can interface with Stan through a variety of computing…
Descriptors: Item Response Theory, Computer Software Evaluation, Computer Software, Programming Languages