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…

Using an RD design provides statistically robust estimates while allowing researchers a different causal estimation tool to be used in educational environments where an RCT may not be feasible. Results from External Evaluation of the i3 Scale-Up of Reading Recovery show that impact estimates were remarkably similar between a randomized control…

Multilevel experiments have been widely used in education and social sciences to evaluate causal effects of interventions. Two key considerations in designing experimental studies are statistical power and the minimal use of resources. Optimal design framework simultaneously addresses both considerations. This dissertation extends previous optimal…

This article describes the analysis of regression-discontinuity designs (RDDs) using the R packages rdd, rdrobust, and rddtools. We discuss similarities and differences between these packages and provide directions on how to use them effectively. We use real data from the Carolina Abecedarian Project to show how an analysis of an RDD can be…

Access to Head Start has been shown to improve children's preschool experiences and school readiness on selected factors through the end of 1st grade. Two more years of follow-up, through the end of 3rd grade, can now be examined to determine whether these effects continue into the middle elementary grades. The statistical design and impact…