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相关论文: Leveraging Local Distributions in Mendelian Random…

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Mendelian randomization (MR) has become an essential tool for causal inference in biomedical and public health research. By using genetic variants as instrumental variables, MR helps address unmeasured confounding and reverse causation,…

统计方法学 · 统计学 2025-11-04 Minhao Yao , Anqi Wang , Xihao Li , Zhonghua Liu

We consider the challenging problem of estimating causal effects from purely observational data in the bi-directional Mendelian randomization (MR), where some invalid instruments, as well as unmeasured confounding, usually exist. To address…

统计方法学 · 统计学 2024-07-15 Feng Xie , Zhen Yao , Lin Xie , Yan Zeng , Zhi Geng

Recent advances in genotyping technology have delivered a wealth of genetic data, which is rapidly advancing our understanding of the underlying genetic architecture of complex diseases. Mendelian Randomization (MR) leverages such genetic…

统计方法学 · 统计学 2023-12-19 Wenhao Cao , Saonli Basu

Mendelian randomization (MR) is a widely-used method to estimate the causal relationship between a risk factor and disease. A fundamental part of any MR analysis is to choose appropriate genetic variants as instrumental variables.…

统计方法学 · 统计学 2023-04-26 Ashish Patel , Francis J. DiTraglia , Verena Zuber , Stephen Burgess

Mendelian randomization (MR) is a popular method in genetic epidemiology to estimate the effect of an exposure on an outcome by using genetic instruments. These instruments are often selected from a combination of prior knowledge from…

统计方法学 · 统计学 2019-11-12 Nan Bi , Hyunseung Kang , Jonathan Taylor

Mendelian randomization (MR) is a powerful method that uses genetic variants as instrumental variables (IVs) to infer the causal effect of a modifiable exposure on an outcome. Although recent years have seen many extensions of basic MR…

统计方法学 · 统计学 2022-03-15 Sai Li , Ting Ye

Estimating the causal effect of an exposure on an outcome is an important task in many economical and biological studies. Mendelian randomization, in particular, uses genetic variants as instruments to estimate causal effects in…

统计方法学 · 统计学 2017-06-06 Sai Li

Mendelian Randomisation (MR) uses genetic variants as instrumental variables to infer causal effects of exposures on an outcome. One key assumption of MR is that the genetic variants used as instrumental variables are independent of the…

统计方法学 · 统计学 2025-02-21 Maximilian M Mandl , Anne-Laure Boulesteix , Stephen Burgess , Verena Zuber

Mendelian randomization is a widely-used method to estimate the unconfounded effect of an exposure on an outcome by using genetic variants as instrumental variables. Mendelian randomization analyses which use variants from a single genetic…

统计方法学 · 统计学 2024-02-20 Ashish Patel , Dipender Gill , Paul J. Newcombe , Stephen Burgess

Mendelian randomization is the use of genetic variants to make causal inferences from observational data. The field is currently undergoing a revolution fuelled by increasing numbers of genetic variants demonstrated to be associated with…

统计方法学 · 统计学 2018-08-31 Stephen Burgess , Jack Bowden , Frank Dudbridge , Simon G Thompson

Our approach to Mendelian Randomization (MR) analysis is designed to increase reproducibility of causal effect "discoveries" by: (i) using a Bayesian approach to inference; (ii) replacing the point null hypothesis with a region of practical…

统计方法学 · 统计学 2022-08-11 Linyi Zou , Teresa Fazia , Hui Guo , Carlo Berzuini

Mendelian randomization (MR) is an instrumental variable (IV) approach to infer causal relationships between exposures and outcomes with genome-wide association studies (GWAS) summary data. However, the multivariable inverse-variance…

统计方法学 · 统计学 2024-02-13 Yihe Yang , Noah Lorincz-Comi , Xiaofeng Zhu

Instrumental variables have been widely used for estimating the causal effect between exposure and outcome. Conventional estimation methods require complete knowledge about all the instruments' validity; a valid instrument must not have a…

统计方法学 · 统计学 2014-09-23 Hyunseung Kang , Anru Zhang , T. Tony Cai , Dylan S. Small

Mendelian randomization (MR) uses genetic variants as instrumental variables to make causal claims. Standard MR approaches typically report a single population-averaged estimate, limiting their ability to explore effect heterogeneity or…

统计方法学 · 统计学 2025-07-16 Stephen Burgess , Benjamin A R Woolf , Amy M Mason

The use of genetic variants as instrumental variables - an approach known as Mendelian randomization - is a popular epidemiological method for estimating the causal effect of an exposure (phenotype, biomarker, risk factor) on a disease or…

统计方法学 · 统计学 2020-12-21 Ioan Gabriel Bucur , Tom Claassen , Tom Heskes

Mendelian randomization is the use of genetic variants as instrumental variables to assess whether a risk factor is a cause of a disease outcome. Increasingly, Mendelian randomization investigations are conducted on the basis of summarized…

应用统计 · 统计学 2015-12-15 Stephen Burgess , Jack Bowden

Mendelian randomization (MR) is widely used to uncover causal relationships in the presence of unmeasured confounders. However, most existing MR methods presuppose linear causality, risking bias when the true relationships are nonlinear,…

统计方法学 · 统计学 2025-08-05 Xinpei Wang , Tao Huang , Jinzhu Jia

Mendelian randomization (MR) is a popular instrumental variable (IV) approach, in which one or several genetic markers serve as IVs that can sometimes be leveraged to recover valid inferences about a given exposure-outcome causal…

统计方法学 · 统计学 2021-08-10 Eric J. Tchetgen Tchetgen , BaoLuo Sun , Stefan Walter

Mendelian randomization (MR) is a method of exploiting genetic variation to unbiasedly estimate a causal effect in presence of unmeasured confounding. MR is being widely used in epidemiology and other related areas of population science. In…

应用统计 · 统计学 2019-01-03 Qingyuan Zhao , Jingshu Wang , Gibran Hemani , Jack Bowden , Dylan S. Small

Mendelian randomization (MR) is a pivotal tool in genetics, genomics, and epidemiology, leveraging genetic variants as instrumental variables to infer causal relationships between exposures and outcomes. Traditional MR methods, while…

统计方法学 · 统计学 2026-01-15 Bitan Sarkar , Yuchao Jiang , Tian Ge , Yang Ni
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