ERIC Number: EJ1178845
Record Type: Journal
Publication Date: 2018-Jun
Pages: 25
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0013-1644
EISSN: N/A
Using the Stan Program for Bayesian Item Response Theory
Luo, Yong; Jiao, Hong
Educational and Psychological Measurement, v78 n3 p384-408 Jun 2018
Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the three-parameter logistic IRT model, the graded response model, and the nominal response model. We demonstrate how IRT model comparison can be conducted with Stan and how the provided Stan code for simple IRT models can be easily extended to their multidimensional and multilevel cases.
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software, Monte Carlo Methods, Comparative Analysis, Markov Processes, Mathematics, Mathematical Models, Equations (Mathematics), Program Implementation, Scores, Statistical Analysis
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
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Authoring Institution: N/A
Grant or Contract Numbers: N/A