Causal inference in four British cohort studies

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.