Statistics in Biomedicine and Health Economics

A research programme that encompasses the development, evaluation, and application of statistical and data science methods to address questions in health research.

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Theme Overview

This theme has a research programme that encompasses the development, evaluation, and application of statistical and data science methods to address questions in health research. The overarching aim is to identify and apply the best possible statistical methods in health research, enabling the translation of reliable research findings to health care.

Much of the work within this theme is interdisciplinary and collaborative. There are established links with clinical and health research groups within UCL and beyond. In particular several staff members have joint posts with the UCLH/UCL Biomedical Research Centre (BRC) and the UCL Primary Care and Mental Health Clinical Trials Unit. There are strong collaborative links with the UCL Department of Applied Health Research, UCL Division of Psychiatry, LSE and Imperial College (Epidemiology and Biostatistics).

Current methodological research topics include risk prediction models, modelling clustered data, multistate models, model selection, survival models, trials methodology, methods for handling missing data, causal inference, regression discontinuity design, analysis of health economic data, multi-omics data integration, statistical / probabilistic genomics; mathematical biology; network models in genomics, and Bayesian Statistics.

This theme includes the Biostatistics Group and the Statistics  for Health Economic Evaluation Group. Researchers from the Statistics for Health Economic Evaluation Group are founding and key members of two international consortia (ConVOI) and R-HTA, working on the development and dissemination of methods for the analysis of the value of information and for the establishment of statistical methods and software in health technology assessment.

Theme Members

Research Groups

  • Biostatistics Group. The Biostatistics Group (BSG) led by Professor Rumana Omar, conducts both collaborative research with health researchers based in UCL and the associated NHS Trusts and research into statistical methodologies required to address the challenges and needs of biomedical research.
  • Statistics for Health Economics Evaluation. The activity of this group revolves around the development and application of Bayesian statistical methodology for health economic evaluation, e.g. cost-effectiveness or cost-utility analysis.

Recent and Upcoming Events

Current and Recent Externally Funded Projects

  • Addressing incomplete data problems arising from integrating multiple data sources (£150k approx. funded by the Alan Turing Institute).
  • Developing a coherent Bayesian modelling and imputation framework that accounts for, and utilises, Structured Missingness (£337k, funded by the Alan Turing Institute).
  • Partial recovery of missing responses - a toolbox for efficient design and analysis when data may be missing not at random (£349k, EPSRC standard grant: EP/V00641X/1).
  • Cancer Intervention and Surveillance Modelling Network (CISNET) Modeling Precision Interventions for Prostate Cancer Control. NIH (£970,000).
  • MRC skills development Fellowship awarded to fund three years’ independent work developing novel statistical methodology for biomedical science applications. (£340 304).
  • Mixed Semi-Continuous Copula Additive Regression Models with Applications in Insurance and Health Care. EPSRC (440,000).
  • Royal Society Wellcome Trust Sir Henry Dale fellowship.
  • Biostatistics Group research grants
  • Statistics for Health Economic Evaluation Group research grants

Research Projects Selected as REF2021 Case Studies