Beyond Generalization: Designing Randomized Experiments to Predict Treatment Effects

November 19, 2023
Much of the focus of methods for generalizing treatment effects has focused on estimation and hypothesis testing regarding a target population average treatment effect (ATE). But generalization is only an issue if treatment effects vary - and if they vary, why not focus on predicting unit-specific treatment effects instead? In this paper, we consider when prediction may be feasible, with a focus on planning studies for such purposes. We consider both cases in which the sample is from the target population and when it is not, and we focus on the use of a parametric linear regression model for these predictions. Doing so results in closed form expressions of error that can be translated into design parameters for use in study design.