New method revolutionizes item response theory parameter estimation for better assessments.
The article explains three methods for estimating parameters in item response theory models: joint maximum likelihood, conditional maximum likelihood, and marginal maximum likelihood. The focus is on how marginal maximum likelihood estimation uses the EM algorithm and Bayesian framework to estimate item parameters. Person parameters are then estimated using this method. Alternative estimation approaches are also briefly mentioned.
