Using Multisite Experiments to Study Cross-Site Variation in Treatment Effects: A Hybrid Approach With Fixed Intercepts and a Random Treatment Coefficient

Abstract

The present article considers a fundamental question in evaluation research: “By how much do program effects vary across sites?” The article first presents a theoretical model of cross-site impact variation and a related estimation model with a random treatment coefficient and fixed site-specific intercepts. This approach eliminates several biases that can arise from unbalanced sample designs for multisite randomized trials. The article then describes how the approach operates, explores its assumptions, and applies the approach to data from three large welfare-to-work trials. The article also illustrates how to report cross-site impact findings and presents diagnostics for assessing these findings. To keep the article manageable, it focuses on experimental estimates of effects of program assignment (effects of intent to treat), although the ideas presented can be extended to analyses of multisite quasi-experiments and experimental estimates of effects of program participation (complier average causal effects).