罗宾斯-布瑞斯勒-格陵兰方差估计的简便方法

Paul Silcocks
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引用次数: 0

摘要

多年来,分层病例对照研究中几率比例(及其对数)的曼特尔-海恩泽尔估计值一直缺乏一个普遍接受的方差估计值。罗宾斯-布雷斯洛-格陵兰估计值满足了这一需求,但标准教科书仍未解释其推导过程。本文提供了一个易于理解的推导过程,展示了罗宾斯-布雷斯罗-格陵兰估计值与我们熟悉的对数几率方差的伍尔夫估计值之间的联系,很容易将其纳入流行病学的硕士课程中。此外,还回顾了无条件最大似然估计和有条件最大似然估计之间的关系。
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An easy approach to the Robins-Breslow-Greenland variance estimator.

The Mantel-Haenszel estimate for the odds ratio (and its logarithm) in stratified case control studies lacked a generally acceptable variance estimate for many years. The Robins-Breslow-Greenland estimate has met this need, but standard textbooks still do not provide an explanation of how it is derived. This article provides an accessible derivation which demonstrates the link between the Robins-Breslow-Greenland estimate and the familiar Woolf estimate for the variance of the log odds ratio, and which could easily be included in Masters level courses in epidemiology. The relationships to the unconditional and conditional maximum likelihood estimates are also reviewed.

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