Correction to “Multivariable MR Can Mitigate Bias in Two-Sample MR Using Covariable-Adjusted Summary Associations”

IF 3.4 4区医学 Q3 GENETICS & HEREDITY

Genetic Epidemiology Pub Date : 2026-02-23 DOI:10.1002/gepi.70035

引用次数: 0

Abstract

Gilbody, J., Borges, M.C., Davey Smith, G. and Sanderson, E. (2025), Multivariable MR Can Mitigate Bias in Two-Sample MR Using Covariable-Adjusted Summary Associations. Genetic Epidemiology, 49: e22606. https://doi.org/10.1002/gepi.22606

In the originally published article, the funding code from the British Heart Foundation was given incorrectly. The correct code is AA/18/1/34219. The online version of this article has been corrected.

We apologize for this error.

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更正“使用协变量调整的汇总关联，多变量MR可以减轻双样本MR的偏差”。

Gilbody， J., Borges, m.c., Davey Smith， G.和Sanderson， E.(2025)，多变量MR可以使用协变量调整的汇总关联来减轻双样本MR的偏差。中华流行病学杂志，49(2):444 - 444。https://doi.org/10.1002/gepi.22606In在最初发表的文章中，来自英国心脏基金会的资助代码是错误的。正确的代码是AA/18/1/34219。本文的在线版本已被更正。我们为这个错误道歉。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Genetic Epidemiology 医学-公共卫生、环境卫生与职业卫生

CiteScore

4.40

自引率

9.50%

发文量

审稿时长

6-12 weeks

期刊介绍： Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations. Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.