The Statistics and Data Science team plays an integral part in the research of all scientific programmes in the MRC Epidemiology Unit.
Statistics work is led by Stephen Sharp:
- Good Analytical Practice.
- Statistical input into ongoing Unit research work.
- Library of exemplar Stata code for application of specific methods.
- Cambridge Epidemiology and Trials Unit (CETU).
- National Diet and Nutrition Survey (NDNS) rolling programme.
- QC, imputation and analysis for big data from genomewide and omics platforms.
- Collaborations with external statisticians (e.g. MRC Biostatistics Unit) on statistical topics of relevance to Unit research.
- Contributions to the training of statisticians and epidemiologists (e.g. University of Cambridge MPhil in Population Health Sciences).
- Provision of statistical reviews for papers submitted to medical and epidemiological journals.
Data science work is led by Tom Bishop:
- Federated meta-analysis, which enables cross-cohort analyses without physically pooling data from each study (InterConnect, EUCAN-Connect projects).
- Application of novel methods for data acquisition and processing, including web-scraping techniques and deep neural networks.
- Collaboration with external experts (e.g. University of Cambridge Department of Applied Mathematics and Theoretical Physics, Department of Computer Science, Health Data Research UK) on data science issues of relevance to Unit research.
- Development of a Trusted Research Environment (TRE) for the Unit, which allows researchers to use and access our data without being able to take it away.