Item Response Theory (IRT) is a widely adopted framework in psychological and educational assessments, used to model the relationship between latent traits and observed responses. This recent work introduces an innovative approach that incorporates group-theoretic symmetry constraints, offering a refined methodology for estimating IRT parameters with greater precision and efficiency. …
Olvera Astivia, Kroc, and Zumbo’s (2020) study examines the assumptions underlying Cronbach’s coefficient alpha and how the distribution of items affects reliability estimation. By introducing a new framework rooted in Fréchet-Hoeffding bounds, the authors offer a fresh perspective on the limitations of this widely used reliability measure. Their work provides …
The study by Shi and Maydeu-Olivares (2020) analyzes how different estimation methods influence key fit indices in Structural Equation Modeling (SEM). By focusing on methods such as Maximum Likelihood (ML), Unweighted Least Squares (ULS), and Diagonally Weighted Least Squares (DWLS), the authors explore the nuances of model fit across various …
Roberts and Thompson (2011) conducted a thorough analysis of item parameter estimation methods within the Generalized Graded Unfolding Model (GGUM). Their work focused on the performance of the Marginal Maximum A Posteriori (MMAP) procedure compared to other approaches, including Marginal Maximum Likelihood (MML) and Markov Chain Monte Carlo (MCMC). By …
