Research areas

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

Methodology

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.