  A causal claim is any assertion that invokes causal relationships between
variables, for example that a drug has a certain effect on preventing a
disease. Causal claims are established through a combination of data and a set
of causal assumptions called a causal model. A claim is robust when it is
insensitive to violations of some of the causal assumptions embodied in the
model. This paper gives a formal definition of this notion of robustness and
establishes a graphical condition for quantifying the degree of robustness of a
given causal claim. Algorithms for computing the degree of robustness are also
presented.
