Generalized Linear Models and Extensions, 2nd Edition
Comment from the Stata technical groupGeneralized linear models (GLMs) extend standard linear (Gaussian) regression techniques to models with a non-Gaussian, or even discrete, response. GLM theory is predicated on the exponential family of distributions—a class so rich that it includes the commonly used logit, probit, and Poisson distributions. Although one can fit these models in Stata by using specialized commands (e.g.,
logit for logit models), fitting them under the GLM paradigm with Stata’s
glm command offers the advantage of having many models under the same roof. For example, model diagnostics may be calculated and interpreted similarly regardless of the assumed distribution.