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Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods
Estimation of individual treatment effect in observational data is complicated due to the challenges of confounding and selection bias. A useful inferential framework to address this is the counterfactual (potential outcomes) model, which takes the hypothetical stance of asking what if an individual...
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| Publicado no: | J Comput Graph Stat |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5920646/ https://ncbi.nlm.nih.gov/pubmed/29706752 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/10618600.2017.1356325 |
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