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Medicine

D-Index
121
Citations
118061
World Ranking
3517
National Ranking
350

Overview

Ian R. White is affiliated with University College London in the United Kingdom. Their research focuses primarily on the field of mathematics, with a specialization in statistics and related areas.

The main fields of study associated with their work include:

  • Mathematics

Within this broad area, their subfields of expertise include:

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty
  • Clinical Psychology
  • Oncology

Key topics covered in their research are:

  • Statistical Methods in Clinical Trials
  • Health Systems, Economic Evaluations, Quality of Life
  • Meta-analysis and systematic reviews
  • Advanced Causal Inference Techniques
  • Statistical Methods and Bayesian Inference
  • Statistical Methods and Inference
  • Delphi Technique in Research

Ian R. White's work is frequently published in several journals and venues, including:

  • Statistics in Medicine
  • arXiv (Cornell University)
  • Trials
  • American Journal of Orthodontics and Dentofacial Orthopedics
  • BMJ

They have collaborated regularly with various coauthors, notably:

  • Brennan C Kahan
  • Tra My Pham
  • Tim P. Morris
  • Matteo Quartagno
  • Sally Hopewell

Recent publications by Ian R. White include:

  • "Missing Data in Clinical Research: A Tutorial on Multiple Imputation," 2020, Canadian Journal of Cardiology
  • "Mindfulness-based programmes for mental health promotion in adults in nonclinical settings: A systematic review and meta-analysis of randomised controlled trials," 2021, PLoS Medicine
  • "CONSORT 2025 statement: updated guideline for reporting randomised trials," 2025, BMJ
  • "The Impact of the COVID-19 Pandemic and Associated Control Measures on the Mental Health of the General Population," 2022, Annals of Internal Medicine
  • "CONSORT 2025 statement: updated guideline for reporting randomised trials," 2025, The Lancet

Best Publications

  • RoB 2: a revised tool for assessing risk of bias in randomised trials.

    Jonathan A.C. Sterne;Jelena Savović;Jelena Savović;Matthew J. Page;Roy G. Elbers

  • Multiple imputation using chained equations: Issues and guidance for practice

    Ian R. White;Patrick Royston;Angela M. Wood

  • Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.

    Jonathan A C Sterne;Ian R White;John B Carlin;Michael Spratt

  • Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

    N Sarwar;P Gao;Seshasai Srk.

  • Health inequalities among British civil servants: the Whitehall II study

    M.G. Marmot;S. Stansfeld;C. Patel;F. North

  • Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality.

    S Erqou;S Kaptoge;PL Perry;E Di Angelantonio

  • Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people.

    Eleni Rapsomaniki;Adam Timmis;Julie George;Mar Pujades-Rodriguez

  • Plasma fibrinogen level and the risk of major cardiovascular diseases and nonvascular mortality: an individual participant meta-analysis.

    J Danesh;S Lewington;S G Thompson;Lowe Gdo.

  • Review of inverse probability weighting for dealing with missing data

    Shaun R Seaman;Ian R White

  • European Society of Contact Dermatitis guideline for diagnostic patch testing – recommendations on best practice

    Jeanne D Johansen;Kristiina Aalto-Korte;Tove Agner;Klaus E Andersen

  • Multiple Imputation by Chained Equations (MICE): Implementation in Stata

    Patrick Royston;Ian R. White

  • C-Reactive Protein, Fibrinogen, and Cardiovascular Disease Prediction

    Stephen Kaptoge;Emanuele Di Angelantonio;Lisa Pennells;Angela M. Wood

  • Imputing missing covariate values for the Cox model.

    Ian R. White;Patrick Royston

  • Strategy for intention to treat analysis in randomised trials with missing outcome data

    Ian R White;Nicholas J Horton;James Carpenter;Stuart J Pocock

  • Using simulation studies to evaluate statistical methods

    Tim P. Morris;Ian R. White;Michael J. Crowther

  • Bias and efficiency of multiple imputation compared with complete‐case analysis for missing covariate values

    Ian R White;John B Carlin;John B Carlin

  • Are missing outcome data adequately handled? A review of published randomized controlled trials in major medical journals:

    Angela M Wood;Ian R White;Simon G Thompson

  • Screening for Fetal Growth Restriction With Universal Third Trimester Ultrasonography in Nulliparous Women in the Pregnancy Outcome Prediction (POP) Study: A Prospective Cohort Study

    Ulla Sovio;Ian R. White;Alison Dacey;Dharmintra Pasupathy

  • Extending DerSimonian and Laird's methodology to perform multivariate random effects meta-analyses.

    Dan Jackson;Ian R. White;Simon G. Thompson

  • A guide to handling missing data in cost-effectiveness analysis conducted within randomised controlled trials.

    Rita Faria;Manuel Gomes;David Epstein;David Epstein;Ian R. White

Frequent Co-Authors

Jeanne D. Johansen
Jeanne D. Johansen Copenhagen University Hospital
Klaus Ejner Andersen
Klaus Ejner Andersen University of Southern Denmark
Torkil Menné
Torkil Menné Copenhagen University Hospital
Dan Jackson
Dan Jackson AstraZeneca (United Kingdom)
Wolfgang Uter
Wolfgang Uter University of Erlangen-Nuremberg
David A. Basketter
David A. Basketter University of Bedfordshire
James R. Carpenter
James R. Carpenter University College London
Julian P T Higgins
Julian P T Higgins University of Bristol
Richard Emsley
Richard Emsley King's College London
Thomas Rustemeyer
Thomas Rustemeyer University of Amsterdam

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