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Adjustment for unmeasured confounding through informative priors for the confounder-outcome relation
BACKGROUND: Observational studies of medical interventions or risk factors are potentially biased by unmeasured confounding. In this paper we propose a Bayesian approach by defining an informative prior for the confounder-outcome relation, to reduce bias due to unmeasured confounding. This approach...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303957/ https://www.ncbi.nlm.nih.gov/pubmed/30577773 http://dx.doi.org/10.1186/s12874-018-0634-3 |