1. Introduction -- Model Specification -- Prerequisites and Preliminaries -- Looking Forward -- 2. The Exponential Family -- Justification -- Derivation -- Canonical Form -- Multiparameter Models -- 3. Likelihood Theory and the Moments -- Maximum Likelihood Estimation -- Calculating the Mean of the Exponential Family -- Calculating the Variance of the Exponential Family -- The Variance Function -- 4. Linear Structure and the Link Function -- The Generalization -- Distributions -- 5. Estimation Procedures -- Estimation Techniques -- 6. Residuals and Model Fit -- Defining Residuals -- Measuring and Comparing Goodness of Fit -- Asymptotic Properties -- 7. Conclusion -- Summary -- Related Topics -- Further Reading -- Motivation
Summary
"The author explains the theoretical underpinnings of generalized linear models so that researchers can decide how to select the best way to adapt their data for this type of analysis. Examples are provided to illustrate the application of GLM to actual data and the author includes his Web address where additional resources can be found."--Pub. desc