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 is particularly interested in developing methods for handling 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. Other interests in trials are in correcting for departures from randomised treatment and in non-inferiority trial design. He runs courses on many of these topics and has written a range of Stata software.
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 Jul 30;
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.
Sullivan TR, White IR, Salter AB, Ryan P, Lee KJ. Should multiple imputation be the method of choice for handling missing data in randomized trials? Stat Methods Med Res. 2016 Dec 19;096228021668357.