Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed at demonstrating DCM analyses with various hierarchical attribute structures via Bayesian estimation using freely available R packages, including CDM and R2jags. We illustrated a step-by-step procedure in R with an eighth-grade mathematics test from the 2007 Trends in International Mathematics and Science Study (TIMSS).
Hsu, Chia-Ling; Chen, Yi-Hsin; and Wu, Yi-Jhen
"Using a Bayesian Estimation to Examine Attribute Hierarchies of the 2007 TIMSS Mathematics Test: A Demonstration Using R Packages,"
Practical Assessment, Research, and Evaluation: Vol. 28, Article 11.
Available at: https://scholarworks.umass.edu/pare/vol28/iss1/11