Webster Thomas F
Dept. of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA.
Environ Health. 2007 Jul 5;6:17. doi: 10.1186/1476-069X-6-17.
As ecologic studies are often inexpensive to conduct, consideration of the magnitude and direction of ecologic biases may be useful in both study design and sensitivity analysis of results. This paper examines three types of ecologic bias: confounding by group, effect measure modification by group, and non-differential exposure misclassification.
Bias of the risk difference on the individual and ecologic levels are compared using two-by-two tables, simple equations, and risk diagrams. Risk diagrams provide a convenient way to simultaneously display information from both levels.
Confounding by group and effect measure modification by group act in the same direction on the individual and group levels, but have larger impact on the latter. The reduction in exposure variance caused by aggregation magnifies the individual level bias due to ignoring groups. For some studies, the magnification factor can be calculated from the ecologic data alone. Small magnification factors indicate little bias beyond that occurring at the individual level. Aggregation is also responsible for the different impacts of non-differential exposure misclassification on individual and ecologic studies.
The analytical tools developed here are useful in analyzing ecologic bias. The concept of bias magnification may be helpful in designing ecologic studies and performing sensitivity analysis of their results.
由于生态研究的开展成本通常较低,在研究设计和结果敏感性分析中考虑生态偏倚的大小和方向可能会有所帮助。本文探讨了三种类型的生态偏倚:群组混杂、群组效应测量修正和非差异性暴露错误分类。
使用二乘二表、简单方程和风险图比较个体水平和生态水平上风险差的偏倚。风险图提供了一种方便的方式来同时展示两个水平的信息。
群组混杂和群组效应测量修正在个体水平和群组水平上的作用方向相同,但对后者的影响更大。由于聚合导致的暴露方差减少会因忽略群组而放大个体水平的偏倚。对于某些研究,放大因子可以仅从生态数据中计算得出。小的放大因子表明除个体水平出现的偏倚外几乎没有其他偏倚。聚合也是非差异性暴露错误分类对个体研究和生态研究产生不同影响的原因。
本文开发的分析工具有助于分析生态偏倚。偏倚放大的概念可能有助于设计生态研究并对其结果进行敏感性分析。