Adjustment for unmeasured confounding through informative priors for the confounder-outcome relation

Adjustment for unmeasured confounding through informative priors for the confounder-outcome relation

Abstract 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 a...

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Bibliographic Details
Main Authors: Rolf H. H. Groenwold, Inbal Shofty, Milica Miočević, Maarten van Smeden, Irene Klugkist
Format: Article
Language:English
Published: BMC 2018-12-01
Series:BMC Medical Research Methodology
Subjects:
Bias
Confounding
Bayesian statistics
Sensitivity analysis
Online Access:http://link.springer.com/article/10.1186/s12874-018-0634-3

Internet

http://link.springer.com/article/10.1186/s12874-018-0634-3

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