A simulation-based comparison of techniques to correct for measurement error in matched case–control studies

A. Guolo,

Corresponding Author

A. Guolo

[email protected]

Department of Statistics, University of Padova, Via Cesare Battisti, 241, I-35121 Padova, Italy

Via Cesare Battisti, 241, I-35121 Padova, ItalySearch for more papers by this author

A. R. Brazzale,

A. R. Brazzale

Department of Social, Cognitive and Quantitative Sciences, University of Modena and Reggio Emilia, Via Antonio Allegri, 9, I-42100 Reggio Emilia, Italy

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A. Guolo,

Corresponding Author

A. Guolo

[email protected]

Department of Statistics, University of Padova, Via Cesare Battisti, 241, I-35121 Padova, Italy

Via Cesare Battisti, 241, I-35121 Padova, ItalySearch for more papers by this author

A. R. Brazzale,

A. R. Brazzale

Department of Social, Cognitive and Quantitative Sciences, University of Modena and Reggio Emilia, Via Antonio Allegri, 9, I-42100 Reggio Emilia, Italy

Search for more papers by this author

First published: 14 April 2008

https://doi.org/10.1002/sim.3282

Citations: 15

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Abstract

The presence of measurement errors affecting the covariates in regression models is a relevant topic in many scientific areas, as, for example, in epidemiology. An example is given by an epidemiological population-based matched case–control study on the aetiology of childhood malignancies, which is currently under completion in Italy. This study was aimed at evaluating the effects of childhood exposure to extremely low electromagnetic fields on the risk of disease occurrence by taking into account the possibility of erroneous measures of the exposure. Within this framework, we focus on the application of likelihood methods to correct for measurement error. This approach, which has received less attention in literature with respect to alternatives, is compared with commonly used methods such as regression calibration and SIMEX. The comparison is performed by simulation, under a broad range of measurement error structures. Copyright © 2008 John Wiley & Sons, Ltd.

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Volume27, Issue19

30 August 2008

Pages 3755-3775

A simulation-based comparison of techniques to correct for measurement error in matched case–control studies

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A simulation-based comparison of techniques to correct for measurement error in matched case–control studies

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