BSU Research overviewMany practical difficulties arise in the analysis of clinical research and epidemiological studies: data are incomplete, patients in clinical trials deviate from their allocated treatment, studies in meta-analyses are heterogeneous and inconsistent, and risk models are developed from small numbers of individuals. These difficulties are often ignored or handled weakly, which can lead to poor conclusions being drawn or to controversy undermining a study's impact. Ian works on finding methods that are well-grounded in statistical theory but which can be applied widely and conveniently in practice. This involves development of methods, writing user-friendly computer software, working with applied collaborators and disseminating good methods through short courses and tutorial articles.
Selected PapersKeogh RH, White IR. (2014)Tutorial in biostatistics: A toolkit for measurement error correction using repeated measures, with a focus on nutritional epidemiology.
Statistics in Medicine 33: 2137–2155
Resche-Rigon M, White IR, Bartlett JW, Thompson SG. (2013)Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data.
Statistics in Medicine 32: 4890-4905
White IR, Barrett JK, Jackson D & Higgins JPT. (2012)Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression.
Research Synthesis Methods 3: 111-125
Jackson D, Mason D, White IR, Sutton S. (2012)An exploration of the missing data mechanism in an Internet based smoking cessation trial.
BMC Medical Research Methodology 12: 157
White IR, Carpenter J, Horton NJ. (2012)Including all individuals is not enough: lessons for intention-to-treat analysis.
Clinical Trials 9: 396-407
White, I. R., Horton, N. J., Carpenter, J. & Pocock, S. J. (2011)Strategy for intention to treat analysis in randomised trials with missing outcome data.
British Medical Journal 2011: 342, d40
White, I. R., Wood, A. & Royston, P. (2011)Tutorial in biostatistics: Multiple imputation using chained equations: issues and guidance for practice.
Statistics in Medicine 30: 377-399
Sterne, J. A. C., White, I. R., Carlin, J. B., Spratt, M., Royston, P., Kenward, M. G., Wood, A. M. & Carpenter, J. R. (2009)Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.
British Medical Journal 338: b2393
White, I. R. (2009)Multivariate random-effects meta-analysis.
Stata Journal 9: 40-56