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.

可用于骨科研究的数据集通常包含由于数据收集错误或数据缺失而导致的测量和错误分类错误。这些错误可能会对研究结果产生不同的影响。测量误差是指连续变量（例如，体重指数）的不准确测量，而错误分类是指将受试者分配到错误的暴露和/或结果组（例如，肥胖类别）。任何类型的错误分类都可能导致低估或高估暴露与结果之间的关联。在本文中，我们提供了避免、识别和解释测量和错误分类错误的实用指南。我们还提供了一个说明性示例，说明如何进行验证研究以解决基于现实世界骨科数据的错误分类问题。请访问以下 https://youtu.be/9-ekW2NnWrs 或视频，以实际方式解释本文的要点。