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.
WEBINAR
Causal inference in four British cohort studies (7 October 2026)
This webinar will introduce key approaches to causal inference when using longitudinal data and explain how to apply these methods within CLS cohort data.
WEBINAR RECORDING
Handling bias in analysis of mixed-mode survey data
30 April 2026
BLOG
Giving a voice to the whole population
30 July 2024
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
Richard Silverwood
Associate Professor and Chief Statistician
Georgia Tomova
Research Fellow (Statistics/Quantitative Social Science)
Liam Wright
Lecturer in Applied Statistical Methodology
Centre for Longitudinal Studies
UCL Social Research Institute
20 Bedford Way
London WC1H 0AL
Email: clsdata@ucl.ac.uk
