The generalized linear/nonlinear model is a generalization of the linear regression model such that 1) nonlinear as well as linear effects can be tested 2) for categorical predictor variables, as well as for continuous predictor variables, using 3) any dependent variable whose distribution follows several special members of the exponential family of distributions (e.g., gamma, Poisson, binomial, etc.), as well as for any normally-distributed dependent variable.

For an overview of the Generalized Linear/Nonlinear Model, see the Introductory Overview for the Generalized Linear/Nonlinear Model (GLZ) method of analysis.