Improving the Estimation of Site-Specific Effects and Their Distribution in Multisite Trials

JoonHo Lee, Jonathan Che, Sophia Rabe-Hesketh, Avi Feller and Luke Miratrix
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JoonHo Lee: The University of Alabama
Jonathan Che: Exponent
Avi Feller: University of California, Berkeley
Luke Miratrix: Harvard University

Journal of Educational and Behavioral Statistics, 2025, vol. 50, issue 5, 731-764

Abstract: In multisite trials, researchers are often interested in several inferential goals: estimating treatment effects for each site, ranking these effects, and studying their distribution. This study seeks to identify optimal methods for estimating these targets. Through a comprehensive simulation study, we assess two strategies and their combined effects: semiparametric modeling of the prior distribution and alternative posterior summary methods tailored to minimize specific loss functions. Our findings highlight that the success of different estimation strategies depends largely on the amount of within-site and between-site information available from the data. We discuss how our results can guide balancing the trade-offs associated with shrinkage in limited data environments.

Keywords: multisite trials; site-specific effects; finite-population estimand; Dirichlet process mixture; constrained Bayes; triple-goal estimator; heterogeneous treatment effects (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:50:y:2025:i:5:p:731-764

DOI: 10.3102/10769986241254286

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