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…

We review the GIDNA and CDM packages in R for fitting cognitive diagnosis/diagnostic classification models. We first provide a summary of their core capabilities and then use both simulated and real data to compare their functionalities in practice. We found that the most relevant routines in the two packages appear to be more similar than…