We promote the development and application of innovative statistical methods and deepen their integration into our population studies.
The rationale is to ensure robust scientific progress by making sound inferences in the presence of uncertainty, and to maximise new insights from our data rich studies. We collaborate extensively with our partners at the MRC Biostatistics Unit, which conducts methodological research.
MRC Biostatistics Unit Priorities
- statistical genomics
- design and analysis of randomised trials (including the £2million MRC Hub for Trial Methodology Research established in 2009)
- evidence synthesis for health
- methods for complex observational and longitudinal data.
An independent study reported that S Thompson’s paper on heterogeneity in meta-analysis was the most cited biostatistics paper of the past decade
To encourage research at the intersection of methodological and applied statistical research, we have created joint appointments between the MRC Biostatistics Unit and the University, including those involving the MRC Cognitive Function and Ageing Study and the Centre for Diet and Activity Research.
There is a critical mass of additional biostatistical research in the Cambridge Institute of Public Health which is cross-linked with the MRC Biostatistics Unit through joint seminars and projects.
risk communication (David Spiegelhalter)
public health modelling (Simon Thompson)
case-cohort methods (Stephen Sharp)
causal inference (Stephen Burgess)
The Professorship of Statistics in Biomedicine was established in 2013, to be a joint appointment between the University and the MRC Biostatistics Unit.
We are now developing further linkages with other world-leading quantitative institutes in Cambridge, most notably the University Statistical Laboratory, the Sanger Institute, and the European Bioinformatics Institute. This objective has been facilitated by the establishment in 2012 of a 4-year Wellcome Trust PhD Programme in Mathematical Genomics and Medicine, which involves collaboration among quantitative scientists in the University, MRC Biostatistics Unit, and the Hinxton Genome Campus.