Professor Kate Tilling
Workstream lead for Large, complex datasets Genetic evidence to prioritise intervention
Kate Tilling is Professor of Medical Statistics and MRC Investigator in the MRC Integrative Epidemiology Unit at the University of Bristol.
She leads a multidisciplinary team of health data scientists developing and applying statistical methods for causal inference.
Her main research interests are in the development and application of statistical methods to causal problems in epidemiology/health services research. Two particular areas are methods for analysis of longitudinal data, and methods for minimising bias due to missing data.
She is part of Bristol BRC’s translational data science theme.
Reducing bias in research: Building better tools to combine study results
When researchers want to know whether something causes a health outcome, like whether a vitamin…
- Theme Translational data science
- Workstream Large, complex datasets
Improving decisions on what to focus on in research using large datasets
Research using de-personalised data from electronic health records is increasingly common. Electronic…
- Theme Translational data science
- Workstream Large, complex datasets
Do ethnicity and coexisting health conditions impact high-risk diabetes?
About a third of people diagnosed with type 2 diabetes have very high blood sugar…
- Theme Translational data science
- Workstreams Clinical informatics platforms Large, complex datasets
Handling missing data in large electronic healthcare record datasets
Electronic healthcare records (EHRs) are created when healthcare professionals record information about the health of…
- Theme Translational data science
- Workstream Large, complex datasets