When analyzing large-scale assessments (LSAs) that use complex sampling designs, it is important to account for probability sampling using weights. However, the use of these weights in multilevel models has been widely debated, particularly regarding their application at different levels of the model. Yet, no consensus has been reached on the best…

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…

This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to…

The rapid expansion of charter schools reflects a growing interest in education reform and school turnaround efforts across the United States. However, national research on charter school performance remains inconclusive. Of particular debate is the impact of transferring from a traditional public school to a charter school on student achievement…

The current study examined the impacts on students' cognitive performance of the key versus ordinary school system in China, using an analytic approach that combines hierarchical linear modeling with propensity score stratification. The results show that students from key schools score significantly higher on a mathematical achievement test than…