When designing cluster-randomized trials (CRTs), one important consideration is determining the proper sample sizes across levels and treatment conditions to cost-efficiently achieve adequate statistical power. This consideration is usually addressed in an optimal design framework by leveraging the cost structures of sampling and optimizing the…

Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…

Background: An efficacy study based on a randomized controlled trial (RCT) was designed to evaluate the impact of ASSISTments on math learning among middle school students, including those from high-needs rural schools. Despite extensive recruitment efforts in 2021 (during the pandemic), only a few schools and their teachers agreed to participate,…

This is a technical report detailing the analytic methods used to assess the effects of a virtual professional learning community (vPLC)-enhanced ASSISTments intervention. The report uses a quasi-experimental design and partially nested regression model to account for clustering and reveals that while overall effects were positive but not…