In this article, JAGS software was systematically introduced to fit common Bayesian cognitive diagnosis models (CDMs), such as the deterministic inputs, noisy ‘and’ gate model, the deterministic inputs, noisy ‘or’ gate model, the linear logistic model, and the log-linear CDM. The unstructured structural model and the higher-order structural model were both employed. We also showed how to extend those models to consider the testlet-effect. Finally, an empirical example was given as a tutorial to illustrate how to use our JAGS code in R. Using JAGS for Bayesian Cognitive Diagnosis Models: A Tutorial

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