Quantitative bias analysis in practice: review of software for regression with unmeasured confounding

BACKGROUND: Failure to appropriately account for unmeasured confounding may lead to erroneous conclusions. Quantitative bias analysis (QBA) can be used to quantify the potential impact of unmeasured confounding or how much unmeasured confounding would be needed to change a study’s conclusions. Curre...

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Detalles Bibliográficos
Autores principales: Kawabata, Emily, Tilling, Kate, Groenwold, Rolf H. H., Hughes, Rachael A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10158211/
https://www.ncbi.nlm.nih.gov/pubmed/37142961
http://dx.doi.org/10.1186/s12874-023-01906-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10158211/
https://www.ncbi.nlm.nih.gov/pubmed/37142961
http://dx.doi.org/10.1186/s12874-023-01906-8

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