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Optimizing Item Parameter Estimation for the Generalized Graded Unfolding Model
Statistical Methods and Data Analysis

Optimizing Item Parameter Estimation for the Generalized Graded Unfolding Model

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 …