Dr. Lee Fawcett

Lecturer in Statistics

Newcastle University

Publications

My main area of research is in extreme value theory, leading to publications in the mainstream statistics literature and more specialised journals in the field of extremes.

I also collaborate with colleagues in the Transport Operations Research Group and the Food and Human Nutrition Research Centre, leading to publications/reports in more applied journals.



Fawcett, L., Thorpe, N., Matthews, J.T. and Kremer, K. (2017). A novel Bayesian hierarchical model for road safety hotspot prediction. Accident Analysis and Prevention, 99, 1, pp. 216-271.

Fawcett, L. and Newman, K. (2017). The storm of the century! Promoting student enthusiasm for applied statistics. Teaching Statistics, 39, 1, pp. 2-13.

Fawcett, L. and Green, A. (2017). Investigating the properties of Bayesian posterior predictive return levels for environmental extremes. Stochastic Environmental Research and Risk Assessment, submitted.

Matthews, J.T., Newman, K., Green, A., Fawcett, L., Thorpe, N. and Kremer, K. (2017). A decision support toolkit to inform road safety investment decisions. Municipal Engineer, submitted.

Fawcett, L. (2017). Using interactive Shiny applications to faciliate research-informed learning and teaching. Journal of Statistics Education, submitted.

Fawcett, L. (2017). The CASE project: evaluation of case-based approaches to learning and teaching in Statistics service courses. Journal of Statistics Education, submitted.

Fawcett, L. and Walshaw, D. (2016). Sea-surge and wind speed extremes: optimal estimation strategies for planners and engineers. Stochastic Environmental Research and Risk Assessment, 30, pp. 463-480.

Fawcett, L., Matthews, J.T., Kremer, K., Thorpe, N., Newman, K., Gelatioto, F., Muench, A. and Hoffmann, T. (2015). A novel approach to collision hotspot identification accounting for regression to the mean and trend. Proceedings of the 13th Annual Transport Practitioners’ Meeting, London, 2015.

Haldar, S., Ross, A.B., Fawcett, L., Bal, W., Beckmann, M., Brandt, K., Draper, J. and Seal, C.J. (2014). Evaluation of alkylresorcinols and mammalian lignans as biomarkers of either wholegrain rye or wholegrain wheat intake in a dose-response intervention study. Submitted to American Journal of Clinical Nutrition.

Slater, P., Thorpe, N. and Fawcett, L. (2014). Getting Value for Money from Investment in Road Safety: Are we Evaluating our Schemes Correctly? Proceedings of the 12th Annual Transport Practitioners’ Meeting, London, 2014.

Fawcett, L. and Walshaw, D. (2013). Estimating the probability of simultaneous rainfall extremes within a region: a spatial approach. Journal of Applied Statistics, DOI: 10.1080/02664763.2013.856872.

Fawcett, L. and Thorpe, N. (2013). Mobile safety cameras: estimating casualty reductions and the demand for secondary healthcare. Journal of Applied Statistics, 40, 11, pp. 2385-2406.

Thorpe, N. and Fawcett, L. (2012). Linking road casualty and clinical data to assess the effectiveness of mobile safety enforcement cameras: a before and after study. BMJ Open, 2: e001304.

Fawcett, L. and Walshaw, D. (2012). Estimating return levels from serially dependent extremes. Environmetrics, 23, 3, pp. 272-283.

Haldar, S., Beckmann, M., Bal, W., Fawcett, L., Ross, A., Brandt K., Draper J. and Seal, C. (2010). Biomarkers of whole-grain intake; contribution of alkylresorcinols and mammalian lignans to the metabolome, FSA.

Fawcett, L. and Walshaw, D. (2008). Bayesian Inference for Clustered Extremes. Extremes, 11, pp. 217-233.

Fawcett, L., Foster, W.H. and Youd, A.J. (2008). Using computer based assessments in a large statistics service course. MSOR Connections, 8, 3, pp. 43-46.

Colligan, J., Thorpe, N., Goulbourne, L.E., Fawcett, L. and McNay, A. (2008). Mobile Speed Cameras and the Demand for Secondary Health Care in Northumbria, Northumbria Safety Camera Partnership.

Fawcett, L. and Walshaw, D. (2007). Improved Estimation for Temporally Clustered Extremes. Environmetrics, 18, 2, pp. 173-188.

Fawcett, L. and Walshaw, D. (2006). A Hierarchical Model for Extreme Wind Speeds. Applied Statistics, 55, 5, pp. 631-646.

Fawcett, L. and Walshaw, D. (2006). Markov Chain Models for Extreme Wind Speeds. Environmetrics, 17, 8, pp. 795-809.

Fawcett, L. (2005). Statistical Methodology for the Estimation of Environmental Extremes. PhD Thesis, University of Newcastle-upon-Tyne.