Power Analyses for Estimation of Complier Average Causal Effects Under Random Encouragement Designs in Education Research: Theory and Guidance

Abstract

Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis methods for such CACE analyses for a range of RCT designs, including nonclustered, clustered, and random block designs. The focus is on behavioral encouragements to promote action, such as text messaging, that are increasingly being tested in education trials. We derive asymptotic distributions of the CACE estimators using generalized estimating equations theory, which underlie the power formulas. We incorporate noncompliance from both the actual receipt of the encouragement and participation itself. An illustrative power analysis provides sample size guidance using an available Shiny R dashboard.