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…

Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…

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…