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This talk introduces a new randomization method for conducting networked experiments. Balanced randomization configuration is one of the most important concerns for successful comparative studies. However, chance imbalance still exists in many traditional experiments. Under the assumption of random dot product graphs, the proposed method generates more balanced assignments of the units to the treatment and control groups compared with the traditional randomization methods. The proposed method can be used for directed or undirected graphs with or without vertex covariate information. In addition, under the linear model setting, the proposed method achieves the optimal randomization balance asymptotically. Numerical studies provide further evidence of the advantages of the proposed method.
Date: Apr 26, 2018
YouTube Link: https://www.youtube.com/watch?v=4vU1Jn1XSz4
Time: 12:00 – 13:00 pm (Central Time)
About the speaker:
Yichen Qin is an Assistant Professor in the Department of Operations, Business Analytics, and Information Systems in the Lindner College of Business at the University of Cincinnati. He earned his Ph.D. degree in Applied Mathematics and Statistics from the Johns Hopkins University in 2013.
- Web: Faculty Website
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