Bias and causal associations in observational research
Bias and causal associations in observational research
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DOI：
10.1016/s0140-6736(02)07451-2
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发表时间：
2002-01-19
期刊：
影响因子：
168.9
通讯作者：
Schulz, KF
中科院分区：
文献类型：
--
作者：
Grimes, DA;Schulz, KF
医学文献的读者需要考虑两种类型的有效性：内部有效性和外部有效性。内部效度意味着研究衡量了它的目的；外部效度是将研究推广到读者的患者的能力。就内部效度而言，所有观察性研究都在某种程度上存在选择偏差、信息偏差和混杂因素。选择偏差源于所研究的群体之间缺乏可比性。信息偏差是由于对暴露、结果或两者的错误确定而导致的。信息偏差的影响取决于其类型。如果一个群体的信息收集方式与另一群体的信息收集方式不同，就会产生偏见。相比之下，非差异性错误分类往往会掩盖真正的差异。混杂是效果的混合或模糊：研究人员试图将暴露与结果联系起来，但实际上测量了第三个因素（混杂变量）的影响。可以通过多种方式控制混杂：限制、匹配、分层和更复杂的多元技术。如果读者无法根据选择、信息或混杂偏见来解释研究结果，那么机会可能是另一种解释。然而，应该最后检查机会，因为这些偏差可以解释非常重要但虚假的结果。区分虚假关联、间接关联和因果关联可能很困难。时间顺序、关联的强度和一致性以及剂量反应效应的证据等标准都支持因果关系。
Readers of medical literature need to consider two types of validity, Internal and external. Internal validity means that the study measured what It set out to; external validity Is the ability to generalise from the study to the reader's patients. With respect to internal validity, selection bias, Information bias, and confounding are present to some degree in all observational research. Selection bias stems from an absence of comparability between groups being studied. Information bias results from Incorrect determination of exposure, outcome, or both. The effect of Information bias depends on Its type. If Information Is gathered differently for one group than for another, bias results. By contrast, non-differential misclassification tends to obscure real differences. Confounding Is a mixing or blurring of effects: a researcher attempts to relate an exposure to an outcome but actually measures the effect of a third factor (the confounding variable). Confounding can be controlled In several ways: restriction, matching, stratification, and more sophisticated multivariate techniques. If a reader cannot explain away study results on the basis of selection, information, or confounding bias, then chance might be another explanation. Chance should be examined last, however, since these biases can account for highly significant, though bogus results. Differentiation between spurious, Indirect, and causal associations can be difficult. Criteria such as temporal sequence, strength and consistency of an association, and evidence of a dose-response effect lend support to a causal link.