School-based evaluations of interventions are increasingly common in education research. Ideally, the results of these evaluations are used to make evidence-based policy decisions for students. However, it is difficult to make generalizations from these evaluations because the types of schools included in the studies are typically not selected randomly from a target population. This paper provides an overview of statistical methods for improving generalizations from intervention research in education. These are presented as a series of steps aimed at improving research design--particularly recruitment--as well as methods for assessing and summarizing generalizability and estimating treatment impacts for clearly defined target populations.