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The Causal Modelling Group comprises statisticians and methodologists at King’s College London interested in drawing causal inferences from study data. Many empirical investigations aim to make causal inferences from observational studies or experiments. Causal questions range from “What would be the benefit of a new treatment?” or “What would be the harm of exposure to a risk factor?” to “How does this treatment/exposure change an outcome?” (effect mediation) or “Who would benefit/be harmed?” (effect moderation).  The latter is of particular relevance in trials of mental health interventions (therapies) where a person’s ability to benefit might depend on baseline characteristics (predictive markers informing stratified medicine) or on aspects of therapy (process variable).  

In our group we discuss how to conceptualise the causal question of interest, review principled methods for estimating such causal parameters – that is explicitly state the assumptions under which inferences are valid, and consider new methods that might allow us to draw causal inferences under weaker assumptions. We are meeting every fourth Wednesday of the month at 11:00am to discuss papers and ongoing work. 



  • Sabine Landau 
  • Cedric Ginestet 

PhD students

  • Ruijie Li