Using Cluster Random Assignment to Measure Program Impacts

Statistical Implications for the Evaluation of Education Programs

| Howard Bloom, Johannes Bos, Suk-Won Lee

Our paper explores the possibility of randomly assigning groups (or “clusters”) of individuals to a program or a control group in order to estimate the impacts of programs designed to affect whole groups. This cluster assignment approach maintains the primary strength of random assignment—the provision of unbiased impact estimates—but has less statistical power than random assignment of individuals, which usually is not possible for programs focused on whole groups. To explore the statistical implications of cluster assignment we: (1) outline the issues involved, (2) present an analytic framework for studying these issues, and (3) apply this framework to assess the potential for using the approach to evaluate education programs targeted on whole schools. Our findings suggest that cluster assignment of schools holds some promise for estimating the impacts of education programs when it is possible to control for the average performance of past student cohorts or the past performance of individual students.