Use and implementation of the complementary log regression model are discussed, integrating various separate applications of the model under the form of a generalized linear model. Some motivation is drawn from cases where an underlying random variable is reduced to a dichotomous form. Estimation and testing are facilitated by recognizing the complementary log as a specific link function within a generalized linear framework. Testing for goodness of link via efficient scores is also discussed.