Beyond Generalization of the ATE: Designing Randomized Trials to Understand Treatment Effect Heterogeneity
Elizabeth Tipton
Abstract
Abstract Researchers conducting randomized trials have increasingly shifted focus from the average treatment effect to understanding moderators of treatment effects. Current methods for exploring moderation focus on model selection and hypothesis tests. At the same time, recent developments in the design of randomized trials have argued for the need for population-based recruitment in order to generalize well. In this paper, we show that a different population-based recruitment strategy can be implemented to increase the precision of estimates of treatment effect moderators, and we explore the trade-offs between optimal designs for the average treatment effect and moderator effects.
Topics & Concepts
ModerationRandomized controlled trialTreatment effectPopulationSelection (genetic algorithm)Average treatment effectGeneralizationEconometricsRandomized experimentFocus (optics)PsychologyComputer scienceEconomicsMedicineStatisticsMathematicsMachine learningSocial psychologyPropensity score matchingMathematical analysisSurgeryOpticsEnvironmental healthTraditional medicinePhysicsAdvanced Causal Inference TechniquesStatistical Methods in Clinical TrialsStatistical Methods and Inference