Regularized Mixture Rasch Model

The mixture Rasch model is a popular for analyzing multivariate binary data. drawback of this that the number estimated parameters substantially increases with an increasing latent classes, which, in turn, hinders interpretability parameters. This article proposes regularized estimation imposes some sparsity structure on class-specific item difficulties. We illustrate feasibility proposed modeling approach by means one simulation study and two simulated case studies.