Policy makers and practitioners are increasingly called upon to make decisions on the basis of scientific evidence, particularly on results from large randomized trials and on the combination of results across many smaller trials (via meta-analysis). My research focuses on the development of statistical methods and tools for making these ‘causal generalizations’. With regards to large randomized trials, I am interested in developing methods to improve their generalizability and external validity, particularly in education and psychology. This includes the development of improved research designs as well as the use of propensity score methods for improved estimation. My research in meta-analysis focuses on methods for modeling and adjusting for dependence between effect sizes. Here my interest is in the development of small-sample adjustments for cluster robust variance estimation – methods that have application not only in meta-analysis but also in economics and survey sampling. To date, my research has been funded by the National Science Foundation, the Institute for Education Sciences, the Spencer Foundation, and the Raikes Foundation.