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Mathematics
UK
2026

D-Index & Metrics

Mathematics

D-Index
88
Citations
74312
World Ranking
84
National Ranking
3

Research.com Recognitions

  • 2026 - Research.com Mathematics in United Kingdom Leader Award
  • 2025 - Research.com Mathematics in United Kingdom Leader Award
  • 2022 - Research.com Mathematics in United Kingdom Leader Award

Overview

Patrick Royston is a researcher affiliated with University College London in the United Kingdom. Their work is primarily situated within the field of mathematics, with a specific focus on statistics and probability. Royston's research intersects several subfields, including cancer research, economics and econometrics, pulmonary and respiratory medicine, as well as radiology, nuclear medicine, and imaging.

Their main topics of research encompass statistical methods in clinical trials, statistical methods and inference, statistical methods and Bayesian inference, advanced statistical methods and models, health systems including economic evaluations and quality of life, advanced causal inference techniques, and cancer genomics and diagnostics.

Royston has contributed to a number of scientific publications, with recent papers including:

  • A simulation study comparing the power of nine tests of the treatment effect in randomized controlled trials with a time-to-event outcome, 2020, Trials
  • A flexible parametric accelerated failure time model and the extension to time-dependent acceleration factors, 2022, Biostatistics
  • State of the art in selection of variables and functional forms in multivariable analysis-outstanding issues, 2020, Diagnostic and Prognostic Research
  • Doug Altman: Driving critical appraisal and improvements in the quality of methodological and medical research, 2020, Biometrical Journal

Royston has frequently published in venues such as The Stata Journal Promoting communications on statistics and Stata, Diagnostic and Prognostic Research, Biostatistics, Trials, and Biometrical Journal.

Throughout their career, Royston has collaborated with several frequent co-authors, including:

  • Willi Sauerbrei
  • Mahesh Parmar
  • Michael J. Crowther
  • Mark Clements
  • Aris Perperoglou

Best Publications

  • 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

  • Analysis of serial measurements in medical research.

    J. N. S. Matthews;D. G. Altman;M. J. Campbell;P. Royston

  • Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling.

    P. Royston;D.G. Altman

  • Multiple Imputation of Missing Values

    Patrick Royston

  • The cost of dichotomising continuous variables

    Douglas G Altman;Patrick Royston

  • Dichotomizing continuous predictors in multiple regression: a bad idea.

    Patrick Royston;Douglas G. Altman;Willi Sauerbrei

  • What do we mean by validating a prognostic model

    Douglas G. Altman;Patrick Royston

  • Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects.

    Patrick Royston;Mahesh K. B. Parmar

  • Prognosis and prognostic research: what, why, and how?

    Karel G M Moons;Patrick Royston;Yvonne Vergouwe;Diederick E Grobbee

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

    Patrick Royston;Ian R. White

  • Prognosis and prognostic research: Developing a prognostic model

    Patrick Royston;Karel G M Moons;Douglas G Altman;Yvonne Vergouwe

  • The use of fractional polynomials to model continuous risk variables in epidemiology.

    Patrick Royston;Gareth Ambler;Willi Sauerbrei

  • Selection of important variables and determination of functional form for continuous predictors in multivariable model building.

    Willi Sauerbrei;Patrick Royston;Harald Binder

  • Multiple imputation of missing values: Update of ice

    Patrick Royston

  • Restricted mean survival time: an alternative to the hazard ratio for the design and analysis of randomized trials with a time-to-event outcome

    Patrick Royston;Mahesh K B Parmar

  • External validation of a Cox prognostic model: principles and methods

    Patrick Royston;Douglas G Altman

  • Imputing missing covariate values for the Cox model.

    Ian R. White;Patrick Royston

  • combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

    Andrea Marshall;Andrea Marshall;Douglas G Altman;Roger L Holder;Patrick Royston

  • The design of simulation studies in medical statistics

    Andrea Burton;Douglas G. Altman;Patrick Royston;Roger L. Holder

  • Multiple imputation of missing values: update

    Patrick Royston

  • The use of fractional polynomials to model continuous risk variables in epidemiology, International Journal of Epidemiology

    P Royston;G Ambler;W Sauerbrei

Frequent Co-Authors

Douglas G. Altman
Douglas G. Altman University of Oxford
Mahesh K. B. Parmar
Mahesh K. B. Parmar University College London
Ian R. White
Ian R. White University College London
Karel G.M. Moons
Karel G.M. Moons Utrecht University
Tom Bourne
Tom Bourne Imperial College London
Nicholas J. Wald
Nicholas J. Wald Queen Mary University of London
John B. Carlin
John B. Carlin University of Melbourne
Andre Pascal Kengne
Andre Pascal Kengne South African Medical Research Council
Joanne F. Aitken
Joanne F. Aitken Cancer Council Queensland
Stuart Campbell
Stuart Campbell University of Cambridge

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