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Bounded, efficient and multiply robust estimation of average treatment effects using instrumental variables
Instrumental variables (IVs) are widely used for estimating causal effects in the presence of unmeasured confounding. Under the standard IV model, however, the average treatment effect (ATE) is only partially identifiable. To address this, we propose novel assumptions that allow for identification o...
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| Publicado no: | J R Stat Soc Series B Stat Methodol |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6051728/ https://ncbi.nlm.nih.gov/pubmed/30034269 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/rssb.12262 |
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