My research focuses on statistical methods to analyse how biomarkers affect the risk of disease (joint modelling of longitudinal and time-to-event data).

I am developing a joint model to understand how Covid-19 antibodies affects the risk of infection after receiving a vaccine.

I graduated from a Masters in Mathematics and Statistics from the University of Oxford in 2020. I then worked as a Statistician on the Covid-19 vaccine trials at the Oxford Vaccine Group, before starting my DPhil in 2021.

• Joint modelling of longitudinal and time-to-event data
• Survival analysis
• Bayesian modelling
• Multiple imputation

I am interested in developing flexible joint models using which can scale to large datasets. I am also keen to learn more about competing risks, interval censoring, causal inference and spatial statistics.

Please get in touch if you're interested in collaborating, or just want to chat!

Phillips, D. J. and Christodoulou, M. D. and Feng, S. and Pollard, A. J. and Voysey, M. and Steinsaltz, D. Improved estimates of COVID-19 correlates of protection, antibody decay and vaccine efficacy waning: a joint modelling approach. medRxiv (2024).