World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
66
Citations
53935
World Ranking
346
National Ranking
20

James R. Carpenter publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where James R. Carpenter sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 219 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

James R. Carpenter D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where James R. Carpenter sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 66 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

James R. Carpenter is affiliated with University College London in the United Kingdom. Their research primarily spans the fields of mathematics and medicine, with significant contributions to subfields including statistics and probability, economics and econometrics, general health professions, public health, environmental and occupational health, and infectious diseases.

The scientist's work focuses on advanced causal inference techniques, statistical methods and Bayesian inference, statistical methods in clinical trials, health systems, economic evaluations, and quality of life, as well as meta-analysis and systematic reviews. Their research topics also cover broader areas related to statistical methods and inference and health, environment, and cognitive aging.

Among recent publications authored or co-authored by James R. Carpenter are:

  • Framework for the treatment and reporting of missing data in observational studies: The Treatment And Reporting of Missing data in Observational Studies framework (2021, Journal of Clinical Epidemiology)
  • Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: A practical guide (2020, Statistics in Medicine)
  • Missing data: A statistical framework for practice (2021, Biometrical Journal)
  • A Comparison of Three Popular Methods for Handling Missing Data: Complete-Case Analysis, Inverse Probability Weighting, and Multiple Imputation (2022, Sociological Methods & Research)
  • Access to routinely collected health data for clinical trials - review of successful data requests to UK registries (2020, Trials)

Frequent co-authors include Suzie Cro, Tim P. Morris, Elizabeth Williamson, Rosie Cornish, and Kate Tilling. These collaborators reflect ongoing partnerships that have produced numerous studies.

James R. Carpenter has published extensively in venues such as Statistics in Medicine, bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), BMJ Open, and Trials, indicating active engagement with both clinical and methodological research communities.

Best Publications

  • ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions.

    Jonathan A. C. Sterne;Miguel A Hernan;Barnaby C Reeves;Jelena Savovic;Jelena Savovic

  • 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

  • Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials

    Jonathan A C Sterne;Alex J Sutton;John P A Ioannidis;Norma Terrin

  • Bootstrap confidence intervals : when, which, what? A practical guide for medical statisticians

    James Carpenter;John Bithell

  • Undue reliance on I(2) in assessing heterogeneity may mislead.

    Gerta Rücker;Guido Schwarzer;James R Carpenter;James R Carpenter;Martin Schumacher

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

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

  • Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

    Anoop D. Shah;Jonathan W. Bartlett;James Carpenter;Owen Nicholas

  • Multiple imputation and its application

    J Carpenter;M Kenward

  • Multiple imputation: current perspectives.

    Michael G Kenward;James Carpenter

  • Missing covariate data in clinical research: when and when not to use the missing-indicator method for analysis

    R. H. H. Groenwold;I. R. White;A. R. T. Donders;J. R. Carpenter

  • REALCOM-IMPUTE Software for Multilevel Multiple Imputation with Mixed Response Types

    James R. Carpenter;Harvey Goldstein;Michael G. Kenward

  • Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model:

    Jonathan W Bartlett;Shaun R Seaman;Ian R White;James R Carpenter

  • Strategies for Multiple Imputation in Longitudinal Studies

    Michael Spratt;James Carpenter;Jonathan A C Sterne;John B Carlin

  • Arcsine test for publication bias in meta-analyses with binary outcomes.

    Gerta Rücker;Gerta Rücker;Guido Schwarzer;James Carpenter;James Carpenter

  • Meta-Analysis with R

    Guido Schwarzer;Gerta Rücker;James R Carpenter

  • Including all individuals is not enough: lessons for intention-to-treat analysis

    Ian R White;James Carpenter;Nicholas J Horton

  • Analysis of Longitudinal Trials with Protocol Deviation: A Framework for Relevant, Accessible Assumptions, and Inference via Multiple Imputation

    James R. Carpenter;James H. Roger;Michael G. Kenward

  • Framework for the treatment and reporting of missing data in observational studies: The Treatment And Reporting of Missing data in Observational Studies framework.

    Katherine J Lee;Kate M Tilling;Rosie P Cornish;Roderick J A Little

  • Effects of training on quality of peer review: randomised controlled trial

    Sara Schroter;Nick Black;Stephen Evans;James Carpenter

  • Sensitivity analysis after multiple imputation under missing at random: a weighting approach.

    James R. Carpenter;Michael G. Kenward;Ian R. White

  • Multiple imputation of covariates by fully conditional specification: accommodating the substantive model

    Jonathan W. Bartlett;Shaun R. Seaman;Ian R. White;James R. Carpenter

Frequent Co-Authors

Michael G. Kenward
Michael G. Kenward London School of Hygiene & Tropical Medicine
Ian R. White
Ian R. White University College London
Elizabeth A. Williamson
Elizabeth A. Williamson London School of Hygiene & Tropical Medicine
Richard W Morris
Richard W Morris University of Bristol
Harvey Goldstein
Harvey Goldstein University of Bristol
Kate Tilling
Kate Tilling University of Bristol
Irwin Nazareth
Irwin Nazareth University College London
Stephen Evans
Stephen Evans University of London
Jonathan A C Sterne
Jonathan A C Sterne University of Bristol
Matthew R. Sydes
Matthew R. Sydes University College London

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