Data-driven testing for sample selection bias
Non-random sample selection is a commonplace amongst many empirical studies and it arises when an output variable of interest is available only for a restricted non-random subsample of data. This
Category Archives: Statistics
Bayesian Methods for Analysing Historic Data
This project will concern (Bayesian) models for the survival time of historic populations. Such models can provide interesting historical insights. For example, we can understand how survival times have increased
Dynamic Social Media Information Extraction
This project concerns the extraction of information from Social Media such as Facebook and Twitter. It will develop methodology to provide an understanding of how sentiments expressed on social media
Regression modelling of competing risks
Motivation: Survival analysis takes into account of whether an event occurs as well as the time to such an event. Right censoring can be due to the occurrence of another
Network meta-analysis of randomized controlled trials
Motivation: A number of treatments may be available to patients with the same health condition. Policy-maker, clinicians and patients may want to know what the optimal treatment is. This requires
Bayesian approach to complex evidence synthesis with medical applications
This project is concerned with the development and application of statistical methods to combine evidence from clinical trials, to produce more reliable estimates, making informed and evidence-based decision for health.
High-Dimensional Big Data Modelling with Applications to Child Health and Forensic Science
This project will build on recent work that developed models that provide clinicians with a better understand of changes in children’s eyes as they get older. The models for visual
Dynamic Social Media Information Extraction
This project will build on recent work concerning the extraction of information from Social Media such as Facebook and Twitter. It will develop methodology to provide a dynamic understanding of