Our studies
We undertake multidisciplinary research on issues that affect all our lives: child development, education, social mobility, health and wellbeing, families and family life, and ageing. We also conduct research into survey methods, and applied statistical methods.
Our applied statistical methods programme specialises in methods for dealing with attrition, causal identification, and data harmonisation.
Our research helps tackle some of the key challenges we face in our society today.
To find out more, explore the links below.
Our applied statistical methods research programme supports and enables users to tackle some of the important challenges in using longitudinal data, including handling missing data, making causal inferences, and dealing with measurement error. We bring together ideas and methods from a number of disciplines, such as statistics, econometrics, psychometrics, epidemiology and computer science.
Our studies are at the forefront of best practice internationally in a range of different areas relating to longitudinal survey methods, and are informed by the most up-to-date evidence available. We share our learning through publications, conferences presentations and our networks. We work closely with the UK survey agencies who carry out the data collection for our studies.
Through the Millennium Cohort Study (MCS) we have been following the lives of over 19, 500 people since they were born in the UK at the turn of the new century. Here you can read our initial findings from the…
The Next Steps Age 25 Sweep has provided valuable insights into the lives of young adults today. A total of 7,707 cohort members took part at this age, enhancing the study’s value as a resource for researchers to gain an…
Using data from the Millennium Cohort Study (MCS), Next Steps, and the National Child Development Study (NCDS), this project investigated the role of aspirations on social reproduction and social mobility across the divides of gender, ethnicity, disability and social class….
This project aimed to investigate how changes in parental employment have affected childhood weight and if/how this effect has been changing over the last five decades. The project was part of the Cross Cohort Research Programme.
This project investigated the influence of work and family status on exercise and sedentary behaviour in childhood and adult life, taking account of intersections with socio-economic position and gender. The project was part of the Cross Cohort Research Programme.
This research project used evidence from all four of our cohort studies to investigate the short- and long-term health impacts of alcohol. The project was part of the Cross Cohort Research Programme.
For this project the research team used machine learning tools to explore whether essays written by 11-year-olds in 1969 provided clues to their economic status, physical activity, health, and cognitive function in later life.
Drawing on data from all four of our cohort studies, this project examined young people’s mental health trajectories today in the context of previous generations. The project was part of the Cross Cohort Research Programme.
Using data from three of our cohort studies, this project aimed to understand how parents’ long-term financial position shapes their children’s outcomes from an early stage. This was part of the Cross Cohort Research Programme.
This project provided empirical evidence on curricula delivery variation in the UK and institutional differences through analysis of Next Steps and linked National Pupil Database data. This was part of our Cross Cohort Research Programme.
Find the latest developments and insights from across all our longitudinal studies.
Our bibliography is a searchable database of published work based on our cohort studies. Search by keyword, author, date range and journal.
Data from our studies are mainly available through the UK Data Service. We run training to support researchers who are interested in using our studies in their work.
Centre for Longitudinal Studies
UCL Social Research Institute
20 Bedford Way
London WC1H 0AL
Email: clsdata@ucl.ac.uk
