  We derive qualitative relationships about the informational relevance of
variables in graphical decision models based on a consideration of the topology
of the models. Specifically, we identify dominance relations for the expected
value of information on chance variables in terms of their position and
relationships in influence diagrams. The qualitative relationships can be
harnessed to generate nonnumerical procedures for ordering uncertain variables
in a decision model by their informational relevance.
