Prof Ferraro’s lecture will discuss data-driven studies that make causal claims of the form, “Having more X makes individuals/ households/ communities/ ecosystems more resilient”. His lecture will ...

In the example above ... a car accident claim? The at-fault driver’s adjusters and attorneys will likely be looking to identify as many parties as possible that played a causal role in the ...

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...

Causal inference is the task of drawing conclusions from data about the effects of treatments and other type of interventions. In epidemiology and clinical research, as well as in many other fields, ...

On February 18, 2025, the First Circuit joined a growing list of circuit courts to hold that “but-for causation” is the correct causation standard ...

Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

Further studies are warranted to explain the underlying mechanisms of this association. Mendelian randomization (MR), using genetic connections to inquire about the causal impact of a risk factor on ...

Background: According to some recent observational studies, the gut microbiota influences atherosclerosis via the gut microbiota-artery axis. However, the causal role of the gut microbiota in ...

Observational studies are critical tools in clinical research and public health response, but challenges arise in ensuring ...