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Combining Multiple Observational Data Sources to Estimate Causal Effects
The era of big data has witnessed an increasing availability of multiple data sources for statistical analyses. We consider estimation of causal effects combining big main data with unmeasured confounders and smaller validation data with supplementary information on these confounders. Under the unco...
Tallennettuna:
| Julkaisussa: | J Am Stat Assoc |
|---|---|
| Päätekijät: | , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2019
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7571608/ https://ncbi.nlm.nih.gov/pubmed/33088006 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2019.1609973 |
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