J. Bowden

发表

Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges.

Jack Bowden, Sofía S Villar, James Wason, 2015, Statistical science : a review journal of the Institute of Mathematical Statistics.

Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

G. Davey Smith, J. Bowden, S. Burgess, 2015, International journal of epidemiology.

Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

G. Davey Smith, J. Bowden, S. Burgess, 2016, Genetic epidemiology.

Epidemiology and Genetic Epidemiology

M. Tobin, P. Burton, J. Bowden, 2004 .

Using Mendelian randomization to determine causal effects of maternal pregnancy (intrauterine) exposures on offspring outcomes: Sources of bias and methods for assessing them

David M. Evans, D. Lawlor, N. Warrington, 2017, Wellcome open research.

Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score

Dylan S. Small, Qingyuan Zhao, D. Small, 2018, The Annals of Statistics.

Mendelian randomization analysis of case‐control data using structural mean models

S. Vansteelandt, J. Bowden, 2011, Statistics in medicine.

Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies1

G. Davey Smith, J. Bowden, S. Burgess, 2016, The American journal of clinical nutrition.

Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic

N. Sheehan, J. Thompson, G. Davey Smith, 2016, International journal of epidemiology.

Automating Mendelian randomization through machine learning to construct a putative causal map of the human phenome

Tom R. Gaunt, P. Flach, O. Davis, 2017, bioRxiv.

Evaluating the potential role of pleiotropy in Mendelian randomization studies

G. Davey Smith, J. Bowden, G. Hemani, 2018, Human molecular genetics.

On Instrumental Variables Estimation of Causal Odds Ratios

S. Vansteelandt, E. Goetghebeur, J. Bowden, 2011, 1201.2487.

BMI as a Modifiable Risk Factor for Type 2 Diabetes: Refining and Understanding Causal Estimates Using Mendelian Randomization

N. Timpson, G. Smith, J. Bowden, 2016, Diabetes.

A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization

N. Sheehan, G. Davey Smith, J. Bowden, 2017, Statistics in medicine.

Inflammatory Biomarkers and Risk of Schizophrenia

B. Horta, F. Hartwig, G. Davey Smith, 2017, JAMA psychiatry.

An examination of multivariable Mendelian randomization in the single sample and two-sample summary data settings

F. Windmeijer, G. Davey Smith, J. Bowden, 2018, bioRxiv.

Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression

N. Sheehan, G. Davey Smith, J. Bowden, 2017, bioRxiv.

Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study

Tom R. Gaunt, Manuel A. R. Ferreira, David M. Evans, 2017 .

Response to Hartwig and Davies

G. Davey Smith, J. Bowden, S. Burgess, 2016, International Journal of Epidemiology.

Education and coronary heart disease: mendelian randomisation study

K. Fischer, F. Hartwig, G. Davey Smith, 2017, British Medical Journal.

Mendelian randomisation analysis of the effect of educational attainment and cognitive ability on smoking behaviour

M. Munafo, G. Davey Smith, J. Bowden, 2019, Nature Communications.

Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption

D. Lawlor, N. Sheehan, J. Thompson, 2018, bioRxiv.

MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations

Tom R. Gaunt, Hashem A. Shihab, N. Timpson, 2016, bioRxiv.

Integrating summarized data from multiple genetic variants in Mendelian randomization: bias and coverage properties of inverse-variance weighted methods

J. Bowden, S. Burgess, 2015, 1512.04486.

Robust instrumental variable methods using multiple candidate instruments with application to Mendelian randomization

F. Dudbridge, J. Bowden, S. Thompson, 2016, 1606.03729.

Age at menarche and adult body mass index: a Mendelian randomization study

N. Sheehan, J. Bowden, C. Minelli, 2018, International Journal of Obesity.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments

Nancy R. Zhang, Qingyuan Zhao, D. Small, 2020, bioRxiv.

An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings

F. Windmeijer, G. Davey Smith, J. Bowden, 2018, bioRxiv.

Biological and clinical insights from genetics of insomnia symptoms

Max A. Little, Samuel E. Jones, J. Lane, 2019, Nature Genetics.

Testing and correcting for weak and pleiotropic instruments in two‐sample multivariable Mendelian randomization

J. Bowden, E. Sanderson, Wes Spiller, 2020, bioRxiv.

A Mendelian Randomization dictionary: Useful definitions and descriptions for undertaking, understanding and interpreting Mendelian Randomization studies

D. Lawlor, F. Hartwig, J. Bowden, 2019 .

Impact of lack-of-benefit stopping rules on treatment effect estimates of two-arm multi-stage (TAMS) trials with time to event outcome

M. Parmar, J. Bowden, P. Royston, 2013, Trials.

A review and re-interpretation of a group-sequential approach to sample size re-estimation in two-stage trials

J. Bowden, A. Mander, 2014, Pharmaceutical statistics.

Unbiased estimation of odds ratios: combining genomewide association scans with replication studies

Jack Bowden, Frank Dudbridge, F. Dudbridge, 2009, Genetic epidemiology.

An optimal stratified Simon two‐stage design

L. Wernisch, J. Bowden, A. Mander, 2016, Pharmaceutical statistics.

Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits

Xiaofeng Zhu, Max A. Little, Richard Emsley, 2016, Nature Genetics.

Two-Sample Instrumental Variable Analyses Using Heterogeneous Samples

Jingshu Wang, Jack Bowden, Dylan S. Small, 2017, Statistical Science.

An Interval Estimation Approach to Selection Bias in Observational Studies

Qingyuan Zhao, J. Bowden, K. Tilling, 2019, 1906.10159.

Confidence intervals for the between-study variance in random-effects meta-analysis using generalised heterogeneity statistics: should we use unequal tails?

D. Jackson, J. Bowden, 2016, BMC Medical Research Methodology.

Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms

Samuel E. Jones, J. Lane, D. Lawlor, 2019, Nature Communications.

Genome-wide association analyses of chronotype in 697,828 individuals provides new insights into circadian rhythms in humans and links to disease

Samuel E. Jones, J. Lane, D. Lawlor, 2018, bioRxiv.

Assessing the Causal Role of Sleep Traits on Glycated Hemoglobin: A Mendelian Randomization Study

Samuel E. Jones, J. Lane, S. Anderson, 2020, medRxiv.

Association between genetically elevated levels of inflammatory biomarkers and risk of schizophrenia: a two-sample Mendelian randomisation study

B. Horta, G. Smith, F. Hartwig, 2017, bioRxiv.

Testing the principles of Mendelian randomization: Opportunities and complications on a genomewide scale

K. Tansey, J. Bowden, M. Taylor, 2017, bioRxiv.

Invited Commentary: Detecting Individual and Global Horizontal Pleiotropy in Mendelian Randomization—A Job for the Humble Heterogeneity Statistic?

G. Smith, G. Davey Smith, J. Bowden, 2018, American journal of epidemiology.

Evaluation of the causal effect of fibrinogen on incident coronary heart disease via Mendelian randomization

Andrew D. Johnson, C. Ward‐Caviness, M. Waldenberger, 2018 .

Genome-wide association analysis of excessive daytime sleepiness identifies 42 loci that suggest phenotypic subgroups

Max A. Little, Samuel E. Jones, J. Lane, 2018, bioRxiv.

Modelling multiple sources of dissemination bias in meta‐analysis

D. Jackson, J. Bowden, S. Thompson, 2010, Statistics in medicine.

Sparse dimensionality reduction approaches in Mendelian randomisation with highly correlated exposures

V. Zuber, J. Bowden, D. Gill, 2022, medRxiv.

Age at puberty and risk of asthma: A Mendelian randomisation study

N. Sheehan, D. Jarvis, G. Davey Smith, 2018, PLoS medicine.

The use of two-sample methods for Mendelian randomization analyses on single large datasets

N. Sheehan, J. Thompson, J. Bowden, 2020, bioRxiv.

Investigating causality in associations between education and smoking: A two-sample Mendelian randomization study

M. Munafo, G. Davey Smith, J. Bowden, 2017, bioRxiv.

Investigating causality in associations between education and smoking: A two-sample Mendelian randomization study

M. Munafo, G. Smith, J. Bowden, 2017, bioRxiv.

Investigating the role of insulin in increased adiposity: Bi-directional Mendelian randomization study

N. Timpson, G. Davey Smith, J. Bowden, 2017, bioRxiv.

(2018). Adiposity-Mortality Relationships in Type 2 Diabetes, Coronary Heart Disease and Cancer Subgroups in the UK Biobank, and Their Modification by Smoking. Diabetes Care , [dc172508].

M. Rutter, J. Bowden, N. Sattar, 2018 .

Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits. Nature Genetics , (2), 274–281.

Max A. Little, J. Lane, I. Vlasac, 2016 .

Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer

E. E. Vincent, M. Munafo, S. Lewis, 2021, Cancer Causes & Control.

Interaction-based Mendelian randomization with measured and unmeasured gene-by-covariate interactions

F. Hartwig, G. Davey Smith, J. Bowden, 2020, medRxiv.

Mendelian Randomization Concerns-Reply.

F. Hartwig, J. Bowden, M. Borges, 2018, JAMA psychiatry.

Title: Biological and clinical insights from genetics of insomnia symptoms Short Title: Insights from genetics of insomnia symptoms

Max A. Little, Heming, Beaumont, 2018 .

Sample-constrained partial identification with application to selection bias

Qingyuan Zhao, J. Bowden, K. Tilling, 2019, Biometrika.

Empirical Bayes estimation of the selected treatment mean for two-stage drop-the-loser trials: a meta-analytic approach

W. Brannath, J. Bowden, E. Glimm, 2014, Statistics in medicine.

Testing for Weak Instruments in Two Sample Summary Data Multivariable Mendelian Randomisation

J. Bowden, E. Sanderson, Wes Spiller, 2021 .

Detecting Individual and Global Horizontal Pleiotropy in Mendelian Randomization—A Job for the Humble Heterogeneity Statistic? American Journal of Epidemiology, 187(12), 2681-2685. [kwy185]

J. Bowden, G. Hemani, George Davey Smith, 2018 .

Triangulating Instrumental Variable, confounder adjustment and Difference-in-Difference methods for comparative effectiveness research in observational data

B. Shields, W. Henley, J. Bowden, 2022, 2202.09164.

Difficulties in Testing the Instrument Strength Independent of Direct Effect Assumption in Mendelian Randomization.

G. Smith, J. Bowden, S. Burgess, 2017, JAMA cardiology.

Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

Max A. Little, J. Lane, S. Anderson, 2019, Nature Communications.

Recent Developments in Mendelian Randomization Studies

George Davey Smith, Jack Bowden, Jie Zheng, 2017, Current Epidemiology Reports.

The confidence interval method for selecting valid instrumental variables

Jack Bowden, Frank Windmeijer, Fernando P. Hartwig, 2019, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Detecting and correcting for bias in Mendelian randomization analyses using Gene-by-Environment interactions

Jack Bowden, George Davey Smith, Wes Spiller, 2017, bioRxiv.

Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption

Fernando Pires Hartwig, Jack Bowden, George Davey Smith, 2017, bioRxiv.

Profile‐likelihood Bayesian model averaging for two‐sample summary data Mendelian randomization in the presence of horizontal pleiotropy

Jack Bowden, Qingyuan Zhao, Chin Yang Shapland, 2020, bioRxiv.

Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

Ralf Bender, Jack Bowden, Oliver Kuss, 2015, Research synthesis methods.

Approximate confidence intervals for moment‐based estimators of the between‐study variance in random effects meta‐analysis

Jack Bowden, Dan Jackson, Rose Baker, 2015, Research synthesis methods.

How does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts?

Jack Bowden, Dan Jackson, Rose Baker, 2010 .

Sensitivity to missing not at random dropout in clinical trials: Use and interpretation of the trimmed means estimator

J. Bowden, K. Tilling, T. Palmer, 2021, medRxiv.

Gaining power and precision by using model–based weights in the analysis of late stage cancer trials with substantial treatment switching

Jack Bowden, Xin Huang, Ian R White, 2015, Statistics in medicine.

Does coffee consumption impact on heaviness of smoking?

M. Munafo, R. Tyndale, P. Rogers, 2017, Addiction.

The MR-Base platform supports systematic causal inference across the human phenome

Valeriia Haberland, Jack Bowden, Tom R. Gaunt, 2018, eLife.

Misconceptions on the use of MR-Egger regression and the evaluation of the InSIDE assumption

J. Bowden, 2017, International journal of epidemiology.

Sensitivity Analyses for Robust Causal Inference from Mendelian Randomization Analyses with Multiple Genetic Variants

Stephen Burgess, Jack Bowden, Simon G. Thompson, 2016, Epidemiology.

On the physical interpretation of a meta-analysis in the presence of heterogeneity and bias: from clinical trials to Mendelian randomization

Chris Jackson, Jack Bowden, J. Bowden, 2015, 1508.03768.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments

Nancy R. Zhang, Dylan S. Small, Qingyuan Zhao, 2020, bioRxiv.

Body mass index and psychiatric disorders: a Mendelian randomization study

Fernando Pires Hartwig, Jack Bowden, George Davey Smith, 2016, Scientific Reports.

Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

Max A. Little, J. Lane, S. Anderson, 2019, Nature Communications.

Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression

Jack Bowden, Cosetta Minelli, Fabiola Del Greco M, 2018, International journal of epidemiology.

Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes

Max A. Little, Samuel E. Jones, J. Lane, 2019, Nature Communications.

Weak and pleiotropy robust sex‐stratified Mendelian randomization in the one sample and two sample settings

J. Bowden, T. McKinley, V. Karageorgiou, 2023, Genetic epidemiology.

GWAS in 446,118 European adults identifies 78 genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

Max A. Little, Samuel E. Jones, J. Lane, 2018, bioRxiv.

The causal effect of educational attainment on Alzheimer’s disease: A two-sample Mendelian randomization study

G. Smith, Y. Ben-Shlomo, J. Bowden, 2017, bioRxiv.

MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations

Hashem A. Shihab, David M. Evans, N. Timpson, 2016, bioRxiv.

Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness

Kyle J. Gaulton, Peter K. Joshi, Sara M. Willems, 2017, Nature Communications.

Estimating the causal effect of BMI on mortality risk in people with heart disease, diabetes and cancer using Mendelian randomization.

M. Rutter, N. Timpson, N. Sattar, 2021, International journal of cardiology.

Meta‐analysis of time‐to‐event data: a comparison of two‐stage methods

Mark C Simmonds, Jayne Tierney, Jack Bowden, 2011, Research synthesis methods.

Unbiased estimation for response adaptive clinical trials

Jack Bowden, Lorenzo Trippa, L. Trippa, 2015, Statistical methods in medical research.

A comparison of heterogeneity variance estimators in simulated random‐effects meta‐analyses

Jack Bowden, Evangelos Kontopantelis, Julian P T Higgins, 2018, Research synthesis methods.

Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data

F. Dudbridge, J. Bowden, C. Barry, 2020, medRxiv.

Accelerated longitudinal designs: An overview of modelling, power, costs and handling missing data

Jack Bowden, Adrian Mander, Sally Galbraith, 2016, Statistical methods in medical research.

Should RECOVERY have used response adaptive randomisation? Evidence from a simulation study

Jack Bowden, Tamir Sirkis, Benjamin Jones, 2021, BMC Medical Research Methodology.

Meta‐analysis and Mendelian randomization: A review

Jack Bowden, Michael V Holmes, J. Bowden, 2019, Research synthesis methods.

The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma

Jack Bowden, Joy Leahy, Susanne Schmitz, 2018, BMC Medical Research Methodology.

Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics

Jack Bowden, Andrew J Copas, Jayne F Tierney, 2011, BMC medical research methodology.

Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease

Andrew D. Johnson, C. Ward‐Caviness, M. Waldenberger, 2018, bioRxiv.

Mendelian randomization incorporating uncertainty about pleiotropy

Jack Bowden, Nuala A Sheehan, Chin Yang Shapland, 2017, Statistics in medicine.

Mendelian randomisation study of body composition and depression in people of East Asian ancestry highlights potential setting-specific causality

R. Freathy, J. Bowden, Zhengming Chen, 2023, BMC Medicine.

The median and the mode as robust meta‐analysis estimators in the presence of small‐study effects and outliers

Fernando Pires Hartwig, Jack Bowden, Julian Pt Higgins, 2020, Research synthesis methods.

Adiposity-Mortality Relationships in Type 2 Diabetes, Coronary Heart Disease, and Cancer Subgroups in the UK Biobank, and Their Modification by Smoking

Heather A. Robinson, M. Rutter, N. Sattar, 2018, Diabetes Care.

The median and the mode as robust meta-analysis methods in the presence of small study effects

Fernando Pires Hartwig, George Davey Smith, Amand Floriaan Schmidt, 2018, bioRxiv.

Mendelian randomisation with coarsened exposures

Qingyuan Zhao, M. Munafo, G. Davey Smith, 2021, Genetic epidemiology.

A simple framework for Mendelian randomisation of latent continuous exposures with discrete measurements

M. J. Tudball, J. Bowden, R. A. Hughes, 2020, medRxiv.

Low Vitamin D Levels and Risk of Incident Delirium in 351,000 Older UK Biobank Participants

D. Melzer, L. Pilling, R. Fortinsky, 2020, Journal of the American Geriatrics Society.

Robust inference in two-sample Mendelian randomisation via the zero modal pleiotropy assumption

Fernando Pires Hartwig, George Davey Smith, Jack Bowden, 2017, bioRxiv.

Assessing causality in associations between cannabis use and schizophrenia risk: a two-sample Mendelian randomization study

M. Munafo, G. Davey Smith, J. Bowden, 2016, Psychological Medicine.

A re-evaluation of the ‘quantile approximation method’ for random effects meta-analysis

Jack Bowden, Dan Jackson, D. Jackson, 2008, Statistics in medicine.

Unbiased Estimation of Selected Treatment Means in Two‐Stage Trials

Jack Bowden, Ekkehard Glimm, J. Bowden, 2008, Biometrical journal. Biometrische Zeitschrift.

Individual patient data meta‐analysis of time‐to‐event outcomes: one‐stage versus two‐stage approaches for estimating the hazard ratio under a random effects model

Jack Bowden, Julian Pt Higgins, Andrew J Copas, 2011, Research synthesis methods.

Navigating sample overlap, winner's curse and weak instrument bias in Mendelian randomization studies using the UK Biobank

G. Smith, J. Bowden, G. Hemani, 2021, medRxiv.

Statin treatment effectiveness and the SLCO1B1*5 reduced function genotype: Long‐term outcomes in women and men

D. Melzer, L. Pilling, J. Bowden, 2021, medRxiv.

Weighing Evidence “Steampunk” Style via the Meta-Analyser

Jack Bowden, J. Bowden, Chris Jackson, 2016, The American statistician.

Collaborative pooled analysis of data on C-reactive protein gene variants and coronary disease: judging causality by Mendelian randomisation

Jack Bowden, Alex P. Reiner, Meena Kumari, 2008 .

Investigating a possible causal relationship between maternal serum urate concentrations and offspring birthweight: a Mendelian randomization study

David M. Evans, R. Freathy, N. Warrington, 2022, medRxiv.

Impact of lack-of-benefit stopping rules on treatment effect estimates of two-arm multi-stage (TAMS) trials with time to event outcome

P. Royston, J. Bowden, B. Choodari-Oskooei, 2013, Trials.

Realising the full potential of MR-PHeWAS in cancer

Jack Bowden, J. Bowden, 2020, British Journal of Cancer.

Biological and clinical insights from genetics of insomnia symptoms

Max A. Little, J. Lane, S. Anderson, 2019, Nature Genetics.

Unbiased estimation in seamless phase II/III trials with unequal treatment effect variances and hypothesis‐driven selection rules

Jack Bowden, David S. Robertson, A. Toby Prevost, 2016, Statistics in medicine.

Conditionally unbiased and near unbiased estimation of the selected treatment mean for multistage drop-the-losers trials

Jack Bowden, Ekkehard Glimm, J. Bowden, 2013, Biometrical journal. Biometrische Zeitschrift.

A multi-stage drop-the-losers design for multi-arm clinical trials

Jack Bowden, Christopher Jennison, Nigel Stallard, 2016, Statistical methods in medical research.

A sensitivity analysis framework for the treatment effect measure used in the meta-analysis of comparative binary data from randomised controlled trials

Jack Bowden, Dan Jackson, Rose Baker, 2012, Statistics in medicine.

Accounting for selection and correlation in the analysis of two-stage genome-wide association studies

Jack Bowden, David S. Robertson, A. Toby Prevost, 2016, Biostatistics.

Connecting Instrumental Variable methods for causal inference to the Estimand Framework

Frank Bretz, Jack Bowden, Bjoern Bornkamp, 2020, Statistics in medicine.

Correcting for bias in the selection and validation of informative diagnostic tests

Jack Bowden, A Toby Prevost, D. Robertson, 2015, Statistics in medicine.

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Jack Bowden, Sofía S Villar, James Wason, 2017, Pharmaceutical statistics.

Response‐adaptive randomization for multi‐arm clinical trials using the forward looking Gittins index rule

Jack Bowden, Sofía S Villar, James Wason, 2015, Biometrics.

188-LB: Type 2 Diabetes Is Genetically Correlated with Multiple Long-Term Conditions but These Correlations Are Only Partly Explained by BMI

D. Melzer, L. Pilling, T. Frayling, 2021, Diabetes.

2016). BMI as a Modifiable Risk Factor for Type 2 Diabetes: Refining and Understanding Causal Estimates Using Mendelian Randomization. Diabetes, 65(10), 3002-3007

N. Timpson, J. Bowden, S. Burgess, 2016 .

Mendelian randomisation analysis of the effect of educational attainment and cognitive ability on smoking behaviour

M. Munafo, G. Davey Smith, J. Bowden, 2019, Nature Communications.

Estimating and visualising multivariable Mendelian randomization analyses within a radial framework

J. Bowden, E. Sanderson, W. Spiller, 2023, medRxiv.

MR-AHC: A fast, efficient and robust method for two-sample summary data Mendelian randomization based on agglomerative hierarchical clustering

J. Bowden, N. Mounier, S. Khalid, 2023, medRxiv.

Biological and clinical insights from genetics of insomnia symptoms

Max A. Little, Heming, Samuel E. Jones, 2018, bioRxiv.

Improving the visualisation, interpretation and analysis of two-sample summary data Mendelian randomization via the radial plot and radial regression

Jack Bowden, Cosetta Minelli, John Thompson, 2017, bioRxiv.

Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression

N. Sheehan, G. Davey Smith, J. Bowden, 2018, International journal of epidemiology.

Education and coronary heart disease: a Mendelian randomization study

K. Fischer, G. Davey Smith, J. Bowden, 2017, bioRxiv.

Incorporating discovery and replication GWAS into summary data Mendelian randomization studies: A review of current methods and a simple, general and powerful alternative

D. Robertson, Z. Kutalik, F. Dudbridge, 2023, bioRxiv.

An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings.

F. Windmeijer, G. Smith, J. Bowden, 2020, International journal of epidemiology.

A Two‐Stage Approach to the Correction of Ascertainment Bias in Complex Genetic Studies Involving Variance Components

J Bowden, J R Thompson, P R Burton, 2007, Annals of human genetics.

Using pseudo‐data to correct for publication bias in meta‐analysis

Jack Bowden, John R Thompson, Paul Burton, 2006, Statistics in medicine.

Mendelian randomization analysis of case‐control data using structural mean models

S. Vansteelandt, J. Bowden, 2011, Statistics in medicine.

Just what the doctor ordered: An evaluation of provider preference-based Instrumental Variable methods in observational studies, with application for comparative effectiveness of type 2 diabetes therapy

B. Shields, J. Bowden, J. Dennis, 2023, 2308.08020.

Invited Commentary Invited Commentary: Detecting Individual andGlobal Horizontal Pleiotropy in Mendelian Randomization—A Job for the Humble Heterogeneity Statistic?

Jack Bowden, Gibran Hemani, George Davey Smith, 2018 .

The Triangulation WIthin a STudy (TWIST) framework for causal inference within pharmacogenetic research

D. Melzer, L. Pilling, J. Bowden, 2021, medRxiv.