This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…

In the absence of clear incentives, achievement tests may be subject to the effect of slipping where item response functions have upper asymptotes below one. Slipping reduces score precision for higher latent scores and distorts test developers' understandings of item and test information. A multidimensional four-parameter normal ogive model was…