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A ROBUST AND EFFICIENT APPROACH TO CAUSAL INFERENCE BASED ON SPARSE SUFFICIENT DIMENSION REDUCTION
A fundamental assumption used in causal inference with observational data is that treatment assignment is ignorable given measured confounding variables. This assumption of no missing confounders is plausible if a large number of baseline covariates are included in the analysis, as we often have no...
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| Τόπος έκδοσης: | Ann Stat |
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| Κύριοι συγγραφείς: | , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
2019
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6588012/ https://ncbi.nlm.nih.gov/pubmed/31231143 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/18-AOS1722 |
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