Suppr超能文献

弱工具变量 Mendelian 随机化研究中因果估计的偏差。

Bias in causal estimates from Mendelian randomization studies with weak instruments.

机构信息

MRC Biostatistics Unit, University of Cambridge, Cambridge, U.K.

出版信息

Stat Med. 2011 May 20;30(11):1312-23. doi: 10.1002/sim.4197. Epub 2011 Mar 22.

Abstract

Mendelian randomization studies using genetic instrumental variables (IVs) are now being commonly used to estimate the causal association of a phenotype on an outcome. Even when the necessary underlying assumptions are valid, estimates from analyses using IVs are biased in finite samples. The source and nature of this bias appear poorly understood in the epidemiological field. We explain why the bias is in the direction of the confounded observational association, with magnitude relating to the statistical strength of association between the instrument and phenotype. We comment on the size of the bias, from simulated data, showing that when multiple instruments are used, although the variance of the IV estimator decreases, the bias increases. We discuss ways to analyse Mendelian randomization studies to alleviate the problem of weak instrument bias.

摘要

孟德尔随机化研究使用遗传工具变量(IVs)现在被广泛用于估计表型对结果的因果关联。即使在必要的基本假设有效的情况下,使用 IV 进行分析的估计值在有限样本中是有偏差的。在流行病学领域,这种偏差的来源和性质似乎理解得很差。我们解释了为什么这种偏差的方向与混杂的观察性关联一致,其大小与工具变量和表型之间的关联的统计强度有关。我们从模拟数据中评论了偏差的大小,表明当使用多个工具变量时,尽管 IV 估计量的方差减小,但偏差增加。我们讨论了分析孟德尔随机化研究的方法,以减轻弱工具变量偏差的问题。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验