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Direct linkLuo, Yong; Jiao, Hong – Educational and Psychological Measurement, 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…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software
Download full textFeng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
DeCarlo, Lawrence T. – Applied Psychological Measurement, 2011
Cognitive diagnostic models (CDMs) attempt to uncover latent skills or attributes that examinees must possess in order to answer test items correctly. The DINA (deterministic input, noisy "and") model is a popular CDM that has been widely used. It is shown here that a logistic version of the model can easily be fit with standard software for…
Descriptors: Bayesian Statistics, Computation, Cognitive Tests, Diagnostic Tests
Kim, Jee-Seon; Bolt, Daniel M. – Educational Measurement: Issues and Practice, 2007
The purpose of this ITEMS module is to provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response models. A brief description of Bayesian inference is followed by an overview of the various facets of MCMC algorithms, including discussion of prior specification, sampling procedures, and methods for evaluating chain…
Descriptors: Placement, Monte Carlo Methods, Markov Processes, Measurement
