A Unified Theory of Regression Adjustment for Design-based Inference

Neyman Seminar
Mar 21, 2018 4:00pm to 5:00pm
1011 Evans Hall
Happening As Scheduled
Under the Neyman causal model, a well-known result is that OLS with treatment-by-covariate interactions cannot harm asymptotic precision of estimated treatment effects in completely randomized experiments. But do such guarantees extend to experiments with more complex designs? This paper proposes a general framework for addressing this question and defines a class of generalized regression...
Joel Middleton, UC Berkeley