One part of COVID-19's staggering impact on education has been to suspend or fundamentally alter ongoing education research projects. This article addresses how to analyze the simple but fundamental example of a multi-cohort study in which student assessment data for the final cohort are missing because schools were closed, learning was virtual,…

Value-added assessment methods have been criticized by researchers and policy makers for a number of reasons. One issue includes the sensitivity of model results across different outcome measures. This study examined the utility of incorporating multivariate latent variable approaches within a traditional value-added framework. We evaluated the…

We explored the usefulness of first and second grade reading measures and responsiveness criteria collected within a response-to-intervention (RtI) framework for predicting reading disability (RD) in third grade. We used existing data from 387 linguistically diverse students who had participated in a longitudinal RtI study. Model-based predictors…

In this article we propose several modeling choices to extend propensity score analysis to clustered data. We describe different possible model specifications for estimation of the propensity score: single-level model, fixed effects model, and two random effects models. We also consider both conditioning within clusters and conditioning across…

Vocabulary knowledge at school entry is a robust predictor of later reading achievement. Many children begin formal reading instruction at a significant disadvantage due to low levels of vocabulary. Until recently, relatively few research studies examined the efficacy of vocabulary interventions for children in the early primary grades (e.g.,…