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 ...

A solid coverage of the most important parts of the theory and application of regression models, and generalised linear models. Multiple regression and regression diagnostics. Generalised linear ...

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

Scaled Dev is the deviance divided by the dispersion parameter. Pr>Scaled Dev is the probability of obtaining a greater scaled deviance statistic than that observed if the null hypothesis is true.