reviewTop 10% cited
Avoiding bias from weak instruments in Mendelian randomization studies
International Journal of Epidemiology · 2011 · Vol. 40(3) · pp. 755–764
Stephen Burgess✉(MRC Biostatistics Unit)Simon G. Thompson(MRC Biostatistics Unit)
Abstract
Weak instrument bias is of practical importance for the design and analysis of Mendelian randomization studies. Post hoc choice of instruments, genetic models or data based on measured F-statistics can exacerbate bias. In particular, the commonly cited rule of thumb that F > 10 avoids bias in IV analysis is misleading.
Genetic Associations and EpidemiologyStatistical Methods in Clinical TrialsAdvanced Causal Inference TechniquesMendelian randomizationObservational studyPoolingStatisticsStatisticCovariateEconometricsType I and type II errorsInstrumental variableStandard error
MeSH terms
Data Interpretation, StatisticalFemaleGenotypeHumansMaleRandom AllocationSensitivity and SpecificityGenetic VariationBiasConfounding Factors, EpidemiologicGenetic Predisposition to DiseaseMendelian Randomization Analysis
Citations
4,042
FWCI
6.60
field-weighted impact
References
41
Percentile
97%
vs. same field & year
Citations per year
Cited by
Multivariable Mendelian Randomization: The Use of Pleiotropic Genetic Variants to Estimate Causal Effects
American Journal of Epidemiology · 2015 · 1,715 citations
Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods
Statistics in Medicine · 2015 · 1,225 citations
An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings
International Journal of Epidemiology · 2018 · 1,128 citations
Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic
International Journal of Epidemiology · 2016 · 1,697 citations
Re: “Multivariable Mendelian Randomization: The Use of Pleiotropic Genetic Variants to Estimate Causal Effects”
American Journal of Epidemiology · 2015 · 1,009 citations
Mendelian Randomization as an Approach to Assess Causality Using Observational Data
Journal of the American Society of Nephrology · 2016 · 2,375 citations
Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression
International Journal of Epidemiology · 2015 · 10,342 citations
The MR-Base platform supports systematic causal inference across the human phenome
eLife · 2018 · 8,152 citations
References
Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology
Statistics in Medicine · 2007 · 4,904 citations
Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak
Journal of the American Statistical Association · 1995 · 3,726 citations
Statistical Analysis With Missing Data
Journal of the American Statistical Association · 1989 · 17,494 citations
Estimation and Inference in Econometrics.
The Economic Journal · 1994 · 5,592 citations
Inflammation, Atherosclerosis, and Coronary Artery Disease
New England Journal of Medicine · 2005 · 8,682 citations
Mendelian randomization: prospects, potentials, and limitations
International Journal of Epidemiology · 2004 · 1,275 citations
‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*
International Journal of Epidemiology · 2003 · 6,297 citations
Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants
International Journal of Epidemiology · 2010 · 1,857 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.
