Research Center for Genes, Environment and Human Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100, Taiwan.
Stat Med. 2011 Apr 30;30(9):1007-17. doi: 10.1002/sim.4151. Epub 2011 Jan 13.
Confounding is a major concern in observational studies. To adjust for confounding bias, the potential confounder(s) for a study must first be identified and measured. But this is not always possible. The unmeasured factors may also exhibit effect modification, and this further complicates the situation. In this paper, the author derives bounding formulas for the bias of unmeasured factors with confounding and effect-modifying potentials. Based on these formulas, the author derives two conditions (for the unmeasured factors) to explain away an observed positive finding: the low-threshold (for the minimum of two parameters related to the unmeasured factors) and the high-threshold (for the maximum) conditions. All these should help researchers make more prudent interpretations of their (potentially biased) results.
混杂是观察性研究中的一个主要关注点。为了调整混杂偏差，必须首先识别和测量研究的潜在混杂因素。但这并不总是可行的。未测量的因素也可能表现出效应修饰作用，这进一步使情况复杂化。在本文中，作者推导出具有混杂和效应修饰潜力的未测量因素的偏差的边界公式。基于这些公式，作者推导出两种条件（针对未测量因素）来解释观察到的阳性发现：低阈值（与未测量因素相关的两个参数中的最小值）和高阈值（最大值）条件。所有这些都应该帮助研究人员更谨慎地解释他们（可能存在偏差的）结果。
