The model is correctly specified, i.e.,
The true conditional probabilities are a logistic
function of the independent variables;
No important variables are omitted;
No extraneous variables are included; and
The independent variables are measured
without error.
2. The cases are independent.
3. The independent variables are not linear
combinations of each other.
Perfect multicollinearity makes estimation
impossible,
While strong multicollinearity makes estimates
imprecise.