There exists a large body of research focused on migration distance, where migration is either the outcome of interest or used as an input variable to model something else. However, there is little consistency in the distance thresholds used: these are often arbitrary, based on administrative boundaries or constrained by definitions available in the dataset. This causes problems with comparison across studies, and in some cases where migration distance is poorly defined could lead to issues with interpretation of results. Using Binary Logistic Regression and drawing on data from the 2011 Census Sample of Anonymised Records for England and Wales, we demonstrate that the odds of migrating vary when considering a range of population characteristics across 16 distance thresholds. We argue that the choice of distance cut-offs needs to be population and context specific and that decisions about these cut-offs should be made carefully as part of the study design.

中文翻译：

---

定义迁移研究的距离阈值

有大量的研究集中在迁移距离上，迁移是感兴趣的结果或用作建模其他事物的输入变量。但是，所使用的距离阈值几乎没有一致性：这些阈值通常是任意的，基于管理边界或受数据集中可用定义的约束。这会导致跨研究的比较出现问题，在某些情况下，迁移距离定义不当可能会导致结果解释出现问题。使用Binary Logistic回归并利用2011年英格兰和威尔士匿名记录人口普查样本中的数据，我们证明，当考虑跨越16个距离阈值的一系列人口特征时，迁移的几率会有所不同。