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Should regression calibration or multiple imputation be used when calibrating different devices in a longitudinal study?


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dc.creatorLoop, Matthew
dc.creatorLotspeich, Sarah
dc.creatorGarcia, Tanya
dc.creatorMeyer, Michelle
dc.date.accessioned2023-06-20T20:27:35Z
dc.date.available2023-06-20T20:27:35Z
dc.date.created2023-06-20
dc.identifier.urihttps://aurora.auburn.edu/handle/11200/50538
dc.identifier.urihttp://dx.doi.org/10.35099/aurora-606
dc.description.abstractIn longitudinal studies, the devices used to measure exposures can change from visit to visit. Calibration studies, wherein a subset of participants is measured using both devices at follow-up, may be used to assess between-device differences (i.e., errors). Then, statistical methods are needed to adjust for between-device differences and the missing measurement data that often appear in calibration studies. Regression calibration and multiple imputation are two possible methods. We compared both methods in linear regression with a simulation study, considering various real-world scenarios for a longitudinal study of pulse wave velocity. Regression calibration and multiple imputation were both essentially unbiased. Regression calibration underestimated the empirical standard error by up to 50%, while multiple imputation underestimated it by at most 30%. Regression calibration was slightly more efficient than multiple imputation when the magnitude of the between device differences at follow-up was small. However, the improved representation of uncertainty from multiple imputation suggests we use it over regression calibration in longitudinal studies where a new device at follow-up might be error-prone compared to the device used at baseline.en_US
dc.publisherAuburn Universityen_US
dc.rightsCreative Commons Attribution 4.0 International (CC-BY)en_US
dc.subjectlongitudinal studyen_US
dc.subjectmeasurement erroren_US
dc.subjectcalibration studiesen_US
dc.titleShould regression calibration or multiple imputation be used when calibrating different devices in a longitudinal study?en_US
dc.typeTexten_US
dc.type.genreWorking Paperen_US
dc.creator.orcid0000-0001-9442-4573en_US

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