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Guided Bayesian imputation to adjust for confounding when combining heterogeneous data sources in comparative effectiveness research
In comparative effectiveness research, we are often interested in the estimation of an average causal effect from large observational data (the main study). Often this data does not measure all the necessary confounders. In many occasions, an extensive set of additional covariates is measured for a...
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| Publicado no: | Biostatistics |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5862356/ https://ncbi.nlm.nih.gov/pubmed/28334230 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biostatistics/kxx003 |
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