Causal inference in four British cohort studies
Date:
07/10/2026
Organised by:
UCL Centre for Longitudinal Studies
Presenter:
Liam Wright, Georgia Tomova, Richard Silverwood
Level:
Entry (no or almost no prior knowledge)
Contact:
CLS Events Team
Email: ioe.clsevents@ucl.ac.uk
Venue: Online
This webinar will introduce key approaches to causal inference when using longitudinal data and explain how to apply these methods within CLS cohort data.
About the event
Join our experts for an overview of the challenges – and opportunities – involved in making causal inferences using data from four national cohort studies based at CLS: 1958 National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Next Steps and Millennium Cohort Study (MCS).
The session will cover:
- The importance of formulating a clear causal research question as the first step of a research project.
- The three main sources of bias that arise when using causal inference methods: confounding, selection, and measurement.
- Use of causal Directed Acyclic Graphs (DAGs) to understand these biases and the assumptions they require.
- Understanding how DAGs can inform subsequent analyses, focusing on the ‘Elaborate Theories’ approach that can be easily applied to CLS cohort data.
- The statistical method of Quantitative Bias Analysis (QBA), which allows researchers to assess whether observed associations reflect bias or true causal effects.
Who should attend?
This webinar is aimed at researchers who want to use CLS cohort data to answer causal research questions.
Researchers at all levels and across disciplines will benefit from this webinar. No prior experience of working with the data is required.
Cost:
Free
Website and registration:
Region:
Greater London
Keywords:
Longitudinal Research , Cohort study, Mixed methods longitudinal research, Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis, Statistical Theory and Methods of Inference, Mixed Methods Data Handling and Data Analysis, causal inference, causal Directed Acyclic Graphs, Quantitative Bias Analysis
Related publications and presentations from our eprints archive:
Longitudinal Research
Cohort study
Mixed methods longitudinal research
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis
Statistical Theory and Methods of Inference
Mixed Methods Data Handling and Data Analysis