Paul Baxter

Research interests

Paul’s research in statistical methods for applied health research involves modern regression methodology including multilevel modelling; partial least squares methods and multivariate imputation for missing data. He focuses on the use of routine data for research. These data have been, and will in the future remain, important for advancing significant health impacts.  Data range from the laboratory bench, where data collected from microarrays produces large volumes of data, through to the bedside, where analysis of outcomes through risk adjustment and casemix modelling are crucial for developing policy.

Background

After studying for a BSc in Mathematics with Economics and a PhD in Statistics at the University of Essex, Paul joined the School of Mathematics, University of Leeds as a Lecturer in Statistics in 2003. He moved to the School of Medicine in 2009 and was promoted to Associate Professor in Biostatistics in 2011.  A Chartered Statistician, his research focuses on gaining insight from large and complex observational health data, especially the development and utilisation of latent variable methods and missing data techniques.