The Biostatistics Group specialises in the application and development of statistical methods for medical and healthcare research. Our members are integral to the School's research, and our broad expertise includes: study designs including clinical trials, prognosis studies, risk prediction modelling, analysis of electronic health records, longitudinal data analysis, Graphical Markov modelling, meta-analysis and evidence synthesis. We provide a range of training courses in these areas, undertake undergraduate and postgraduate teaching, and supervise PhD students.

Areas of expertise

We have methodological expertise in a range of areas relevant to the applied healthcare research, including:

  • Clinical trials methodology – design, analysis, and ethics; pilot and feasibility studies
  • Big data analytics using medical record databases and data linkage
  • Prognostic modelling and risk prediction
  • Meta-analysis, including network meta-analysis, multivariate meta-analysis and meta-analysis of IPD
  • Longitudinal data analysis and growth modelling of patient outcome trajectories
  • Time series analysis
  • Latent variable analysis in the construction and psychometric testing of measurement instruments
  • Graphical Markov modelling
  • Non-proportional hazards frailty modelling

Please see staff pages for the interests of individuals.

Aims and strategy

We aim to conduct high-quality applied and methodological research that improves health outcomes and enhances the quality and conduct of healthcare research.

We use robust statistical methods and principles to underpin evidence-based research for primary care, health sciences and other areas of medicine, including secondary care. We collaborate with research groups across different medical fields, both within and external to the School of Medicine and the University. We develop, rigorously test and publish novel statistical methods, and accompanying software modules, for the biostatistics field.

Our aim is realised by

  • ensuring scientific rigour in the methods applied to the design and analysis of randomised controlled trials, prognosis research studies, electronic health record research, and other complex observational studies;
  • developing methods of measurement for creating new health outcomes in clinical research;
  • conducting cutting-edge methodological research into novel statistical methods for the design and analysis of prognosis studies, including those for prognostic models and stratified care (precision medicine);
  • devising and applying new methods for collecting and analysing individual participant data (IPD) across multiple studies for meta-analysis and evidence synthesis;
  • using electronic health records (eHealth) and applying/developing statistical methods that under-pin research in this area of Big Data analytics;
  • developing and delivering novel training courses and building capacity in areas related to our methodological expertise, especially in the areas of clinical trials, IPD meta-analysis, prognostic models and risk prediction, prognosis research, and item response theory (IRT).