You construct a generalized linear model by deciding on response and explanatory variables for your data and choosing an appropriate link function and response probability distribution. Some examples ...

GENMOD uses maximum likelihood estimation to fit generalized linear models. This family includes models for categorical data such as logistic, probit, and complementary log-log regression for binomial ...

The second part [Generalized Regression Methods] provides a further discussion of violations of the classical assumptions including measurement error, omitted variables, simultaneity, missing data; ...