Mixtures of Berkson and classical covariate measurement error in the linear mixed model: bias analysis and application to a study on ultrafine particles

  • The ultrafine particle measurements in the Augsburger Umweltstudie, a panel study conducted in Augsburg, Germany, exhibit measurement error from various sources. Measurements of mobile devices show classical possibly individual–specific measurement error; Berkson–type error, which may also vary individually, occurs, if measurements of fixed monitoring stations are used. The combination of fixed site and individual exposure measurements results in a mixture of the two error types. We extended existing bias analysis approaches to linear mixed models with a complex error structure including individual–specific error components, autocorrelated errors, and a mixture of classical and Berkson error. Theoretical considerations and simulation results show, that autocorrelation may severely change the attenuation of the effect estimations. Furthermore, unbalanced designs and the inclusion of confounding variables influence the degree of attenuation. Bias correction with the method of momentsThe ultrafine particle measurements in the Augsburger Umweltstudie, a panel study conducted in Augsburg, Germany, exhibit measurement error from various sources. Measurements of mobile devices show classical possibly individual–specific measurement error; Berkson–type error, which may also vary individually, occurs, if measurements of fixed monitoring stations are used. The combination of fixed site and individual exposure measurements results in a mixture of the two error types. We extended existing bias analysis approaches to linear mixed models with a complex error structure including individual–specific error components, autocorrelated errors, and a mixture of classical and Berkson error. Theoretical considerations and simulation results show, that autocorrelation may severely change the attenuation of the effect estimations. Furthermore, unbalanced designs and the inclusion of confounding variables influence the degree of attenuation. Bias correction with the method of moments using data with mixture measurement error partially yielded better results compared to the usage of incomplete data with classical error. Confidence intervals (CIs) based on the delta method achieved better coverage probabilities than those based on Bootstrap samples. Moreover, we present the application of these new methods to heart rate measurements within the Augsburger Umweltstudie: the corrected effect estimates were slightly higher than their naive equivalents. The substantial measurement error of ultrafine particle measurements has little impact on the results. The developed methodology is generally applicable to longitudinal data with measurement error.show moreshow less

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Metadaten
Author:Veronika Deffner, Helmut Küchenhoff, Susanne Breitner, Alexandra Schneider, Josef CyrysGND, Annette Peters
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/102365
ISSN:0323-3847OPAC
Parent Title (English):Biometrical Journal
Publisher:Wiley
Place of publication:Weinheim
Type:Article
Language:English
Year of first Publication:2018
Release Date:2023/02/28
Tag:Statistics, Probability and Uncertainty; General Medicine; Statistics and Probability
Volume:60
Issue:3
First Page:480
Last Page:497
DOI:https://doi.org/10.1002/bimj.201600188
Institutes:Fakultätsübergreifende Institute und Einrichtungen
Fakultätsübergreifende Institute und Einrichtungen / Wissenschaftszentrum Umwelt