Programme and Abstracts

Laura Bonnett (University of Liverpool)

is a Medical Statistician (Tenure Track Fellow) primarily interested in the development and validation of prognostic models for people with recurrent conditions such as epilepsy and asthma. She is based in the Department of Biostatistics at the University of Liverpool. Laura’s work has informed the Driving and Vehicle Licensing Agency’s regulations on time off driving for people with a first ever seizure, and driving during and after antiepileptic drug withdrawal. This work has now also underpinned European Union policy on driving. Additionally, Laura is a member of the Royal Statistical Society (RSS) Education Committee and a committed STEM (Science, Technology, Engineering & Mathematics) Ambassador. As part of these roles Laura develops statistical outreach activities which can be used by anyone with an interest in the area at a variety of events such as careers fairs, science festivals and in STEM clubs (www.rss.org.uk/hands-on).

Philip Dawid (University of Cambridge)

is Emeritus Professor of Statistics, University of Cambridge. For many years he was Professor of Probability and Statistics at University College London. He was Editor of Biometrika and of the Journal of the Royal Statistical Society (Series B). He is an elected Fellow of the Royal Society, of IMS, of ISI and of ISBA, and has served as Vice-President of RSS and as President of ISBA, of which he is an honorary lifetime member. Other honours include the Snedecor and DeGroot Prizes, and RSS Guy Medals in Bronze and Silver. His research interests include logical foundations of Bayesian and other schools of probability and statistics, Bayes nets, statistical causality, probability forecasting, and forensic inference.

Fiona Steele (London School of Economics)

is a social statistician with research interests in the development of statistical methods that are motivated by social science problems. Her areas of expertise include longitudinal data analysis, multilevel modelling, survival analysis, and simultaneous equations modelling. She has worked on a range of applications in demography, education, family psychology, and health.

She has directed several research grants funded by the Economic and Social Research Council (ESRC), including the LEMMA node of the National Centre for Research Methods. Her most recent project focuses on methods for the analysis of longitudinal dyadic data, with applications to a study of intergenerational exchanges of support using panel data from the UK Household Longitudinal Study.

She was elected a Fellow of the British Academy in 2009.

Personal website: http://stats.lse.ac.uk/steele/

Harvey Goldstein (University of Bristol)

was formerly Professor of Statistical Methods at the Institute of Education from 1997-2005 and before that a senior researcher at the National Children’s Bureau where he worked extensively on the design and analysis of the NCDS. He is currently Professor of Social Statistics at the University of Bristol where he has a part time appointment and also a part time professorial appointment at the UCL institute of Child health and is a visiting professor at the London School of Hygiene. He is a visiting professor at the Australian catholic University (Brisbane) for the period 2014-2018.

He has been a member of the Council of the Royal Statistical Society, and chair of its Educational Strategy Group. He has been a joint editor of the Journal of the Royal statistical Society, series A (2015-2018). He was awarded the RSS Guy medal in silver in 1998 and was elected a fellow of the British Academy in 1997. He has been the principal applicant on several major ESRC funded research projects since 1981.

He has several research interests. One is in the use of statistical modelling techniques in the construction and analysis of educational tests with a particular interest in institutional and international comparisons. He has written extensively on the use (and misuse) of item response modelling in educational testing and the use and abuse of performance indicators (league tables) in the public sector. He also retains an interest in fitting of complex growth curve models, and he has helped to develop efficient methods for handling missing data and measurement errors in complex models including multilevel ones, and ways of estimating reliabilities in educational test scores. He has helped to develop procedures for unbiased and efficient record linkage of large datasets and procedures for maintaining data integrity while ensuring privacy in the release and analysis of big data sets.

The second, more extensive, interest is in the methodology of multilevel modelling. His major recent book, Multilevel Statistical Models (Wiley, 2011, 4^th edition) is the standard reference text in this important area of statistical data analysis.