Cluster-robust inference methods are a mainstay of applied econometrics and quantitative program evaluation work. However, conventional cluster-robust methods have performance limitations that can be difficult to detect in practice. I will survey some recent proposals for how to refine cluster-robust methods and discuss applications in a range of educational research contexts, including program evaluation, meta-analysis, and single-case research.

Send an email to tsdusick@wisc.edu to register by Thursday, Feb. 19!

You will receive information on how to join the virtual session prior to the lecture.