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A comparison of sensitivity-specificity imputation, direct imputation and fully Bayesian analysis to adjust for exposure misclassification when validation data are unavailable

Corbin, Marine; Haslett, Stephen; Pearce, Neil; Maule, Milena; Greenland, Sander

Description

Purpose: Measurement error is an important source of bias in epidemiological studies. We illustrate three approaches to sensitivity analysis for the effect of measurement error: imputation of the ‘true’ exposure based on specifying the sensitivity and specificity of the measured exposure (SS); direct imputation (DI) using a regression model for the predictive values; and adjustment based on a fully Bayesian analysis. Methods: We deliberately misclassify smoking status in data from a...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Journal article
URI: http://hdl.handle.net/1885/217788
Source: International Journal of Epidemiology
DOI: 10.1093/ije/dyx027

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