Identification of confounder in epidemiologic data contaminated by measurement error in covariates

Identification of confounder in epidemiologic data contaminated by measurement error in covariates

Abstract Background Common methods for confounder identification such as directed acyclic graphs (DAGs), hypothesis testing, or a 10 % change-in-estimate (CIE) criterion for estimated associations may not be applicable due to (a) insufficient knowledge to draw a DAG and (b) when adjustment for a tru...

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Bibliographic Details
Main Authors: Paul H. Lee, Igor Burstyn
Format: Article
Language:English
Published: BMC 2016-05-01
Series:BMC Medical Research Methodology
Subjects:
Causal effect
Change-in-estimate
Confounding
Simulation
Model-selection
Epidemiology
Online Access:http://link.springer.com/article/10.1186/s12874-016-0159-6

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http://link.springer.com/article/10.1186/s12874-016-0159-6

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