Causal Inference with Measurement Errors: with Applications to Experimental and Observational Studies
Measurement errors cause problems in causal inference. However, except for canonical cases, researchers rarely realize the existence of measurement errors in their studies. As a result, they sometimes fail to adjust for them. By combining tools drawn from the literature on machine learning, causal i...
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| Format: | Praca dyplomowa |
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Massachusetts Institute of Technology
2022
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| Dostęp online: | https://hdl.handle.net/1721.1/140173 |