Incompatibility of Model Specifications in Generalized Linear Models

The choice of regression models can vary depending on a study’s objectives and the characteristics of the dataset. Yet it is crucial to recognize that the properties of conditional expectation impose a natural consistency requirement on the formulation of these models. This paper endeavors to demonstrate that, even under the most favorable assumptions concerning the covariates’ structure, inconsistent specifications can arise in generalized linear models, particularly when nonlinear link functions are employed.