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Robust Experimental Designs for Measuring Spillover Effects in Large Networked Populations — NSF Award to University of Chicago (I

This research project will investigate the role of networks in influencing the outcomes of interventions across various domains, such as education, marketing, and tax decisions. Traditional analytic approaches have depended heavily on statistical modeling assumptions. These models have limitations due to the complexity

Award titleRobust Experimental Designs for Measuring Spillover Effects in Large Networked Populations
Award ID2419009
AwardeeUniversity of Chicago
CityCHICAGO
StateIL
Amount obligated$350,000
Principal investigatorPanagiotis Toulis
ProgramHuman Networks & Data Sci Res, Methodology, Measuremt & Stats
Start date08/15/2024
AbstractThis research project will investigate the role of networks in influencing the outcomes of interventions across various domains, such as education, marketing, and tax decisions. Traditional analytic approaches have depended heavily on statistical modeling assumptions. These models have limitations due to the complexity of relationships among individuals. This project will focus on randomized experiments that incorporate network considerations into the experimental design. New methodologies will
SourceNSF Awards

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