The lifecourse epidemiology group develop and apply methodologies that illuminate the complexity of developmental change and continuity, especially in childhood and adolescence. We collaborate with a wide range of groups and use data from multiple longitudinal cohorts, all of which provide unique insights into different aspects of development. We study complex interventions and use longitudinal structural equation models (SEMs) to answer explanatory questions leading to richer information about the effects of interventions.
Causal inference in life course epidemiology including mediation analysis with SEM, g-computation in longitudinal cohorts and randomised trials, and Mendelian Randomisation.
Prognostic modelling and modelling uncertainty in predictions of individual outcomes or trajectories.
Characterising developmental mechanisms in typical and atypical populations by applying SEM to longitudinal cohorts with deep phenotyping (e.g., neurobiological and cognitive data) and therapeutic mechanisms in trials of complex interventions.
The lifecourse epidemiology group hosts the SEMantics seminar series which features applications, methodological advances, best practice, and cautionary tales about SEM. Click here to find out more and view our upcoming seminars.
Professor of Biostatistics and Psychological Methods