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Measurement error correction using validation data: a review of methods and their applicability in case-control studies

Department of Epidemiology, University of Ulm, Germany

Donna Spiegelman

Departments of Biostatistics and Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA

Maria Blettner

Department of Epidemiology and Statistics in Medicine, University of Bielefeld, Germany

Carsten Heuer

SAP AG, Walldorf, Germany

Hermann Brenner

Department of Epidemiology, University of Ulm and Department of Epidemiology, German Centre for Research on Ageing, University of Heidelberg, Germany, brenner{at}dzfa.uni-heidelberg.de

Measurement error is a serious problem in the analysis of epidemiological data. In the past 20 years, a large number of methods for the correction of measurement error have been developed. While at the beginning mostly methods for cohort studies were considered, recently more attention has been paid to case-control studies. Although a variety of methods have been proposed, they are very rarely used in practice. To stimulate their use and further development, this article provides a comprehensive overview on methods developed for multivariable regression analysis of epidemiologic studies with validation data sets. The methods are systematically classified with respect to the underlying theory. An assessment of prerequisites, assumptions and performance of the available methods is given. Particular attention is paid to applicability to case-control studies and need for further research and development is pointed out.

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