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Level: BSc, MSci, MSc
Title: A statistical analysis of GP prescription data
Supervisor:

Dr Silvia Liverani

Research Area: Probability and Applications [Including Statistics]
Description:

In 2011, under an agenda of transparency and open data, a vast amount of healthcare data has been made available to the public via the NHS Digital website. In this project, the student will analyse the data on the number of GP prescriptions across the country. The analysis could focus on a particular group of medicines such as antibiotics, antidepressants or pain-relief medicines, and would investigate whether there is variation in GP prescriptions across years and across regions of the UK. If a variation is found, the project would investigate what factors contribute to this variation, using appropriate regression models. Given the discrete nature of the response variable, this project could involve the use of generalised linear models with discrete response and multi-level models.
Further Reading:
Key Modules:

MTH5120 Statistical Modelling

MTH6134 Statistical Modelling II

MTH5122 Statistical Methods

MTH6136 Statistical Theory

MTH6909/MTH709U/MTHM042/MTH776P Bayesian Statistics

MTH6931/MTH731U/MTHM731 Computational Statistics.

(have passed or be currently attending at least two of the above modules)
Other Information:

Programming skills are a prerequisite for this project, as well as willingness to learn to use the statistical software R. Prior knowledge of R is not a prerequisite.

Current Availability: Yes