Correlation is not Causation! But how can we find answers to questions like "How effective is a given treatment in preventing a disease" or "Did global warming cause this heat wave" based on available ...
Causal inference in observational settings seeks to estimate the effect of exposures, treatments or interventions on outcomes in the absence of random assignment. Unlike experimental designs, ...
Bristol Medical School offer a comprehensive programme of live online short courses, run by subject experts. All courses grant continued access to the course materials and recordings for 5 months ...
Bayesian networks are probabilistic graphical models that encode conditional dependencies among variables within a directed acyclic graph. In the context of causal inference, these networks provide a ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results