On this page:
CLS’ applied statistical methods research programme supports and enables users to tackle some of the important challenges in using longitudinal data.
We bring together ideas and methods from a number of disciplines. These include statistics, econometrics, psychometrics, epidemiology and computer science.
Handling missing data
Discover what missing data are and how to handle them appropriately. Explore our guidance, user guides and training webinars.
Handling mode effects
Find out about how to handle mode effects and prevent bias. Explore our guidance, user guides and training webinars.
Richard is Associate Professor of Statistics and currently holds the post of Chief Statistician at CLS. Richard’s applied work is mainly in non-communicable disease epidemiology and health behaviours, while his methodological interests cover missing data, the analysis of linked administrative data, and causal inference. At CLS, Richard makes major contributions to the Applied Statistical Methods and Survey Methods programmes, in addition to contributing to the work of maintaining, developing and promoting the CLS cohort studies, and advising on other statistical matters.
Brian Dodgeon
Research Fellow
Martina Narayanan
Research Fellow
George Ploubidis
Professor of Population Health and Statistics, and Director of the National Child Development Study and 1970 British Cohort Study
Georgia Tomova
Research Fellow (Statistics/Quantitative Social Science)
Liam Wright
Lecturer in Applied Statistical Methodology
