Hierarchical loglinear models express the logarithm of cell probabilities as a sum of effects. The fullest loglinear model includes a constant, the main effects of each variable, and all two and higher-order interactions. This model is known as the saturated model because it has as many parameters as there are cells in the table, and thus fits the data perfectly