Ian White, Professor of Statistical Methods for Medicine

Ian is a medical statistician with an interest in developing new methodology for design and analysis of clinical trials, meta-analysis and observational studies. He joined the Unit in 2017 after spending 16 years as a programme leader at the Medical Research Council's Biostatistics Unit in Cambridge.

Ian chairs the Unit’s Methodology theme, which comprises four programmes of trial-related research: Design, Conduct, Analysis and Meta-analysis. He leads the Design programme and co-leads the Analysis and Meta-analysis programmes.

Ian is particularly interested in methods for design of non-inferiority and other trials, including the non-inferiority frontier for non-inferiority trials with uncertain control event rate, the personalised randomised controlled trial (PRACTical) for settings without an accepted standard of care, and the combination of factorial and multi-arm multi-stage trials. Other interests in trials are in causal inference, for example to correct for departures from randomised treatment.

He has worked for many years in missing data, where he has contributed to the widespread use of multiple imputation and is now developing extensions for missing-not-at-random data. He is also particularly interested in meta-analysis and network meta-analysis, where he has developed methods for assessing and testing inconsistency. He co-wrote a tutorial on simulation studies.

Ian runs courses on many of these topics for the MRC Clinical Trials Unit at UCL and externally. He has also written a range of Stata software.

Selected publications

Riley RD, Jackson D, Salanti G, Burke DL, Price M, Kirkham J, et al. Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples. BMJ. 2017 Sep 13;j3932.

Jackson D, White IR. When should meta-analysis avoid making hidden normality assumptions? Biometrical J. 2018; 60:1040-1058. doi:10.1002/bimj.201800071

Tompsett DM, Leacy F, Moreno-Betancur M, Heron J, White IR. On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice. Stat Med. 2018 Apr 2;37(15).

Jackson D, Law M, Stijnen T, Viechtbauer W, White IR. A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio. Stat Med. 2018;37(7):1059–85.

Audigier V, White IR, Jolani S, Thomas PA, Quartagno M, Carpenter J, et al. Multiple imputation for multilevel data with continuous and binary variables. Stat Sci. 2018;33:160–83.

White IR, Turner RM, Karahalios A, Salanti G. A comparison of arm‐based and contrast‐based models for network meta‐analysis. Stat Med. 2019;38:5197-5213. doi:10.1002/sim.8360

Morris TP, White IR, Crowther MJ. Using simulation studies to evaluate statistical methods. Stat Med. 2019;38(11):2074-2102. doi:10.1002/sim.8086

Quartagno M, Walker AS, Babiker AG, et al. Handling an uncertain control group event risk in non-inferiority trials: non-inferiority frontiers and the power-stabilising transformation. Trials. 2020;21(1):145. doi:10.1186/s13063-020-4070-4



You can access the latest versions of his Stata software by typing (in Stata):

net from http://www.homepages.ucl.ac.uk/~rmjwiww/stata/

Research Interests

  • Trial design
  • Handling missing data
  • Statistical methods for meta-analysis and network meta-analysis
  • Causal inference in randomised trials
  • Simulation studies

Research Areas