Institute of Clinical Trials and Methodology


Research areas

Most PhD projects are of methodological or statistical nature. You can see some of our areas of interest below.


A priority of the Institute is the development of methods which have a direct impact on the design, conduct or analysis of our or other people’s studies. Our underpinning methodology work is presented in three themes:

Design of trials, meta-analyses and observational studies

  • Multi-arm, multi-stage (MAMS) platform trials
  • Designing phase II (and III trials) based on an enhanced decision process at the end of phase II
  • Improving the design of stratified medicine trials and biomarker validation studies
  • Designing trials in uncommon diseases
  • Cluster randomised and stepped wedge trials
  • A flexible framework for complex time-to-event outcome trials
  • Planning and accounting for missing data
  • Improving the analysis and design of trials with longitudinal data or clusters of varying size
  • Designing trials with recurrent events as the primary outcome measure
  • Re-randomising patients into trials
  • Design, development and validation of prognostic models

Effective and efficient conduct of trials and meta-analyses

  • Providing practical examples of how novel designs can be implemented
  • Evaluating and implementing strategies to ensure that data on randomised patients is not lost through patient withdrawal
  • Efficient trial monitoring
  • Getting trials started more quickly, and facilitating prompt reporting of outcome data

Analysis of trials, meta-analyses and observational studies

  • Analysing multi-arm multi-stage (MAMS) trials
  • Analysing time-to-event outcomes
  • Multivariable prognostic models and treatment-covariate interactions (including validation)
  • Appropriate analysis of longitudinal and clustered data
  • Causal models for answering questions not addressed by randomisation
  • Missing data and improved sensitivity analysis for missing outcome data
  • Design, development and validation of prognostic models

Current projects

  • The "acutely sick" African child: applying new statistical methods to delineate mortality risks and identify ways to improve management - E. George
  • Avoiding bias and learning more from the analysis of longitudinal data - O. Stirrup

Past projects

  • Design issues and extensions of multi-arm multi-stage clinical trials - D. Bratton, 2014
  • Practical and theoretical considerations of the application of marginal structural models to estimate causal effects of treatment in HIV infection - F. Ewing, 2013
  • Sample size for multivariable prognostic models - R. Jinks, 2012
  • Practical use of multiple imputation - T. Morris, 2014

If you are interested in pursuing a PhD in any of the research areas currently pursued above, you should first send a summary of your research interests as well as a copy of your CV (with details of your previous studies) to ictm.phd@ucl.ac.uk. The ICTM Graduate Tutor will help you to identify a potential supervisor, with whom you can then discuss a potential project.

More information