Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding
Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding
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DOI：
10.1136/bmj.330.7498.1021
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发表时间：
2005-04-30
影响因子：
105.7
通讯作者：
Anderson, GM
中科院分区：
文献类型：
--
作者：
Normand, SLT;Sykora, K;Anderson, GM
本系列之前的文章12认为，队列研究存在选择偏倚和混杂因素，批判性评估需要仔细评估研究设计和识别潜在的混杂因素。本文描述了两种分析策略-回归和分层-可用于评估和减少混淆。一些队列研究在混杂因素的基础上对干预组和对照组中的个体参与者进行匹配，但由于匹配可能被视为分层的特殊情况，我们没有专门讨论它，详情可从其他地方获得。这些技术都不能消除与未测量或未知混杂因素相关的偏差。此外，两者都有自己的假设、优势和局限性。
The previous articles in this series 1 2 argued that cohort studies are exposed to selection bias and confounding, and that critical appraisal requires a careful assessment of the study design and the identification of potential confounders. This article describes two analytical strategies—regression and stratification—that can be used to assess and reduce confounding. Some cohort studies match individual participants in the intervention and comparison groups on the basis of confounders, but because matching may be viewed as a special case of stratification we have not discussed it specifically and details are available elsewhere. 3 4 Neither of these techniques can eliminate bias related to unmeasured or unknown confounders. Furthermore, both have their own assumptions, advantages, and limitations.