  this article illustrates the use of linear and bilinear random effects models
to represent statistical dependencies that often characterize dyadic data such
as international relations. In particular, we show how to estimate models for
dyadic data that simultaneously take into account: regressor variables and
third-order dependencies, such as transitivity, clustering, and balance. We
apply this new approach to the relations among ph.d. of university in Iran over
the period from 1991-2005, illustrating the presence and strength of second and
third-order statistical dependencies in these data.
