At University of Southampton, I built a Monte Carlo simulation framework in R to compare fixed and Bayesian adaptive randomisation in two-arm clinical trials. Across 48,000+ simulated trials, Bayesian randomisation allocated 83% of participants to the superior arm versus 50% with fixed randomisation, with a power cost of up to 15 percentage points.
For my clinical trial survival analysis project, I fitted Cox proportional hazards models to a 197-patient diabetic retinopathy trial. I also compared methods for tied survival times and assessed a Weibull accelerated failure time model as an alternative to Cox regression.
I'm studying for an MSc in Medical Statistics and Data Science at University College London (UCL), following a BSc in Mathematics with Actuarial Science from University of Southampton. My projects have also included lung cancer survival analysis using SAS and Python, with ECOG performance status emerging as the strongest predictor in the Cox model.

