Dr Manuela Quaresma
Assistant Professor
London School of Hygiene & Tropical Medicine
15-17 Tavistock Place
London
WC1H 9SH
United Kingdom
I am a medical statistician specialised in survival analysis, small area-estimation, and visualisation techniques, with strong methodological expertise and extensive experience in cancer research. My work integrates the development and use of advanced statistical models with a deep understanding of cancer epidemiology, providing meaningful insights from large-scale, complex cancer datasets. I seek to contribute to the evidence base that informs decision-making and improves cancer care and outcomes in England.
Affiliations
Centres
Teaching
I enjoy teaching for the MSc in Medical Statistics at LSHTM. I co-organise and teach the modules 'Introduction to Statistical Computing' and 'Survival Analysis'. I also teach SAS computing for the module 'Advanced Research Methods'.
Other MSc modules I was involved with in the past include: 'Foundations of Statistics (Probabilities)' and 'Bayesian Analysis' from the MSc in Medical Statistics, and the module 'Statistics for Epidemiology and Population Health' taught on several intensive MSc courses at LSHTM.
Between 2006-2019, I taught on the LSHTM short course 'Cancer Survival: Principles, Methods and Applications' covering topics such as, survival analysis, excess hazard modelling, age standardisation and data visualisation.
I tutor MSc students and supervise MSc projects for the MSc in Medical Statistics.
I co-supervised a PhD student from the Faculty of Epidemiology and Population Health at LSHTM (2018-2020).
Research
I am currently funded by the Cancer Research UK programme investigating "Inequalities in Cancer Care and Outcomes". My focus is on statistical methodology for the analysis of cancer registration data augmented with various electronic health records, with a particular emphasis on cancer survival and excess hazard methods.
I am especially interested in the topics:
- Inequalities in cancer care and outcomes
- Cancer epidemiology
- Net survival methodology
- Excess hazard modelling
- Bayesian analysis
- Spatial analysis
- Quantitative evaluation of interventions
- Stata, R and SAS programming
- Data visualisation
- Cancer registration data
- Analysis of Electronic Health Records
Selected Publications
