如何使用不同的调查数据收集模式引入偏见? 介绍使用定向非循环图 (DAG) 的模式效应
Georgia D Tomova1, Richard J Silverwood1, Peter W G Tennant2
1Centre for Longitudinal Studies, University College London, London, United Kingdom.
American journal of epidemiology
|January 23, 2026
概括
混合模式调查,结合不同的数据收集方法,提出了模式效应和模式选择等挑战. 幼稚的条件化可以引入偏见,突出了流行病学中先进偏见分析的需要.
科学领域:
- 流行病学 流行病学
- 调查方法 调查方法
- 生物统计学 生物统计学
背景情况:
- 调查数据在流行病学中至关重要,传统上通过单一模式收集.
- 混合模式的调查设计 (例如,在线和面对面) 越来越普遍.
- 这种转变带来了挑战:模式效应 (差异物品响应) 和模式选择 (差异参与).
研究的目的:
- 在混合模式调查中引入模式效应和模式选择的挑战.
- 在使用简单的调节方法时,探索碰撞机偏差的潜力.
- 讨论对流行病学研究的影响,并建议偏见分析方法.
主要方法:
- 使用定向非循环图 (DAG) 来可视化数据结构和因果关系.
- 探索混合模式调查设计产生的潜在数据结构.
- 讨论了处理模式效应的基于条件和归算的方法.
主要成果:
- 标准方法,如调节测量模式,可以减少模式效应,但可能会引入碰撞机偏差.
- 模式效应和模式选择之间的相互作用可能导致流行病学研究中的偏见被低估.
- 定量偏差分析被提出为解决这些问题的宝贵工具.
结论:
- 混合模式调查需要仔细考虑模式效应和选择偏差.
- 纯粹的统计调整可以引入新的偏差,特别是碰撞器偏差.
- 定量偏差分析提供了一种强大的方法来减轻混合模式调查数据分析中的偏差.
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