errors due to errors in data collection or missing data. These errors can have different
effects on the study results. Measurement error refers to inaccurate measurement of
continuous variables (eg, body mass index), whereas misclassification refers to assigning
subjects in the wrong exposure and/or outcome groups (eg, obesity categories). Misclassification
of any type can result in underestimation or overestimation of the association between
exposures and outcomes. In this article, we offer practical guidelines to avoid, identify,
and account for measurement and misclassification errors. We also provide an illustrative
example on how to perform a validation study to address misclassification based on
real-world orthopedic data. Please visit the following or videos that explain the highlights of the article in practical terms.
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Published online: September 05, 2022
Received in revised form:
In Press Journal Pre-Proof
One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to https://doi.org/10.1016/j.arth.2022.05.025.
Funding: This work was funded by a grant from the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) grant P30AR76312 and the American Joint Replacement Research-Collaborative (AJRR-C). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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