Added a new method for single time-point analyses (cross-sectional
data), which enables researchers to investigate how the covariates are
associated with attribute mastery. The steps involved in the three-step
approach are: (1) fitting a CDM, (2) assigning examinees to latent
classes and computing the CEPs, and (3) estimating the logistic
regression model with the CEPs. This method was proposed in Iaconangelo
(2017) and was adopted in a cross-sectional analysis of digital literacy
assessment data in Liang et al (2021) <doi:
10.1016/j.chb.2021.106850>. References: Iaconangelo, C. (2017). Uses
of classification error probabilities in the three-step approach to
estimating cognitive diagnosis models (Doctoral dissertation).
https://rucore.libraries.rutgers.edu/rutgers-lib/55495/PDF/1/play/
Liang, Q., de la Torre, J., & Law, N. (2021). Do background
characteristics matter in children’s mastery of digital literacy? A
cognitive diagnosis model analysis. Computers in Human Behavior, 122,
106850. https://doi.org/10.1016/j.chb.2021.106850