Stephen Burgess
Stephen Burgess
University of Cambridge, MRC Biostatistics Unit
Verified email at - Homepage
Cited by
Cited by
Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression
J Bowden, G Davey Smith, S Burgess
International journal of epidemiology 44 (2), 512-525, 2015
Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator
J Bowden, G Davey Smith, PC Haycock, S Burgess
Genetic epidemiology 40 (4), 304-314, 2016
The MR-Base platform supports systematic causal inference across the human phenome
G Hemani, J Zheng, B Elsworth, KH Wade, V Haberland, D Baird, ...
elife 7, e34408, 2018
Mendelian randomization analysis with multiple genetic variants using summarized data
S Burgess, A Butterworth, SG Thompson
Genetic epidemiology 37 (7), 658-665, 2013
Interpreting findings from Mendelian randomization using the MR-Egger method
S Burgess, SG Thompson
European journal of epidemiology 32, 377-389, 2017
Avoiding bias from weak instruments in Mendelian randomization studies
S Burgess, SG Thompson, Crp Chd Genetics Collaboration
International journal of epidemiology 40 (3), 755-764, 2011
Genomic atlas of the human plasma proteome
BB Sun, JC Maranville, JE Peters, D Stacey, JR Staley, J Blackshaw, ...
Nature 558 (7708), 73-79, 2018
MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data
OO Yavorska, S Burgess
International journal of epidemiology 46 (6), 1734-1739, 2017
PhenoScanner V2: an expanded tool for searching human genotype–phenotype associations
MA Kamat, JA Blackshaw, R Young, P Surendran, S Burgess, J Danesh, ...
Bioinformatics 35 (22), 4851-4853, 2019
Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies
AM Wood, S Kaptoge, AS Butterworth, P Willeit, S Warnakula, T Bolton, ...
The Lancet 391 (10129), 1513-1523, 2018
PhenoScanner: a database of human genotype–phenotype associations
JR Staley, J Blackshaw, MA Kamat, S Ellis, P Surendran, BB Sun, ...
Bioinformatics 32 (20), 3207-3209, 2016
Guidelines for performing Mendelian randomization investigations: update for summer 2023
S Burgess, GD Smith, NM Davies, F Dudbridge, D Gill, MM Glymour, ...
Wellcome open research 4, 2019
Bias due to participant overlap in two‐sample Mendelian randomization
S Burgess, NM Davies, SG Thompson
Genetic epidemiology 40 (7), 597-608, 2016
Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variants
S Burgess, J Bowden, T Fall, E Ingelsson, SG Thompson
Epidemiology 28 (1), 30-42, 2017
Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects
S Burgess, SG Thompson
American journal of epidemiology 181 (4), 251-260, 2015
A review of instrumental variable estimators for Mendelian randomization
S Burgess, DS Small, SG Thompson
Statistical methods in medical research 26 (5), 2333-2355, 2017
Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors
S Burgess, RA Scott, NJ Timpson, G Davey Smith, SG Thompson, ...
European journal of epidemiology 30, 543-552, 2015
Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators
BL Pierce, S Burgess
American journal of epidemiology 178 (7), 1177-1184, 2013
Association of cardiometabolic multimorbidity with mortality
E Di Angelantonio, S Kaptoge, D Wormser, P Willeit, AS Butterworth, ...
Jama 314 (1), 52-60, 2015
Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods
S Burgess, F Dudbridge, SG Thompson
Statistics in medicine 35 (11), 1880-1906, 2016
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