Generalized linear models are a type of statistical model that can be used to analyze different types of data. These models are an extension of traditional linear models and are useful for understanding relationships between variables. By using maximum likelihood estimation, researchers can estimate parameters in these models. Diagnostic statistics and model checking methods can help ensure the accuracy of the models. In some cases, using a transformation may be more effective than using generalized linear models for making inferences.