Abstract
We demonstrate delicate but important differences between two types of transformation. The first transformation is by a link function which transforms expectations of observations to their linear predictors in context of the generalized linear model. The second is common transformation of observations themselves, such as Box-Cox's one. We can combine these two types of transformation into a double transformation model. Through the extended model we check which type of transformation is appropriate to several sets of practical data.
