Students in the Detroit Public Community Schools District (DPSCD) have the highest rate of chronic absence (missing 10% or more of school days) among large districts in the United States. Additionally, students in DPSCD are among the poorest students in the country, often lacking access to reliable personal transportation or public transit to…

Research shows teacher influence in school decision-making is related to improving individual job satisfaction and professional commitment. However, few empirical studies investigate how different domains of school decision-making may have a distinct relationship with both individual teacher job satisfaction and professional commitment. Using the…

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…

Level 3 characteristics are increasingly important for fingerprint identification, particularly when the fingerprints are problematic and lack level 2 details. In practice, no reliable visualization methods for level 3 features are transferred into a course for the general public, forensic students, or investigators. Our group has reported the…

Common methods of measuring discipline disproportionality can produce contradictory results and obscure base-rate information. In this paper, we show how using multilevel modeling to analyze discipline disparities resolves ambiguities inherent in traditional measures of disparities: relative rate ratios and risk differences. One previous study…

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…

Common methods of measuring discipline disproportionality can produce contradictory results and obscure base-rate information. In this paper, we show how using multilevel modeling to analyze discipline disparities resolves ambiguities inherent in traditional measures of disparities: relative rate ratios and risk differences. One previous study…