5 different reasons why it’s important to include pre-treatment variables when designing and analyzing a randomized experiment (or doing any causal study)

In presenting causal inference and randomized experiments, we start with the basic framework in which there are pre-treatment predictors x, treatment z, and outcome y, with potential outcomes y(z). Here it is in Regression and Other Stories: Our presentation is … Continue reading → …