Measurement Error and Misclassification in Orthopedics: When Study Subjects are Categorized in the Wrong Exposure or Outcome Groups |
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Institution: | 1. Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona;2. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota;3. Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota |
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Abstract: | Datasets available for orthopedic research often contain measurement and misclassification 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 https://youtu.be/9-ekW2NnWrs or videos that explain the highlights of the article in practical terms. |
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Keywords: | measurement error misclassification orthopedics arthroplasty bias validation |
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