Learning Causal Effects From Many Randomized Experiments Using Regularized Instrumental Variables
Scientific and business practices are increasingly resulting in large collections of randomized experiments. Analyzed together multiple experiments can tell us things that individual experiments cannot. We study how to learn causal relationships between variables from the kinds of collections faced...
Main Authors: | Peysakhovich, Alexander, Eckles, Dean Griffin |
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Other Authors: | Sloan School of Management |
Format: | Article |
Published: |
ACM Press
2021
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Online Access: | https://hdl.handle.net/1721.1/129382 |
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