This paper shows that the LOGIT type stochastic assignment/stochastic user equilibrium assignment can be represented as an optimization problem with only link variables. The conventional entropy function defined by path flows in the objective can be decomposed into a function consisting only of link flours. The idea of the decomposed formulation is derived from a consideration of the most likely link flow patterns over a network. Then the equivalence of the decomposed formulation to LOGIT assignment is proved by using the Markov properties that underlie Dial's algorithm. Through the analyses, some useful properties of the entropy function and its conjugate dual function (expected minimum cost function) have been derived. Finally, it is discussed that the derived results have a potential impact on the development of efficient algorithms for the stochastic user equilibrium assignment.