Covers Generalized Linear Models, likelihood, deviance, link functions, sampling methods, Poisson regression, over-dispersion, and alternative regression models.
Explores special examples of Generalized Linear Models, covering logistic regression, count data models, separation issues, and nonparametric relationships.