Cargando…
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...
Autores principales: | Kawabata, Emily, Tilling, Kate, Groenwold, Rolf H. H., Hughes, Rachael A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
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 |
Ejemplares similares
-
Adjustment for unmeasured confounding through informative priors for the confounder-outcome relation
por: Groenwold, Rolf H. H., et al.
Publicado: (2018) -
To Adjust or Not to Adjust? When a “Confounder” Is Only Measured After Exposure
por: Groenwold, Rolf H. H., et al.
Publicado: (2021) -
Assessing Techniques for Quantifying the Impact of Bias Due to an Unmeasured Confounder: An Applied Example
por: Barberio, Julie, et al.
Publicado: (2021) -
The ACCE method: an approach for obtaining quantitative or qualitative estimates of residual confounding that includes unmeasured confounding
por: Smith, Eric G.
Publicado: (2015) -
Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses
por: Mathur, Maya B., et al.
Publicado: (2019)