We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...

Causal inference is known to be very challenging when only observational data are available. Randomized experiments are often costly and impractical and in instrumental variable regression the number ...

Dr Vanessa Didelez is a statistician developing methods to understand better causal mechanisms, the processes linking cause and effect in complex systems in motion that evolve over time, so-called ...

We consider the problem of model selection and accounting for model uncertainty in high-dimensional contingency tables, motivated by expert system applications. The approach most used currently is a ...