Foundations of Linear and Generalized Linear Models

Foundations of Linear and Generalized Linear Models, 1st Edition, serves as a textbook for upper-undergraduate and graduate students in statistics and biostatistics, as well as a reference for practicing statisticians. It offers an authoritative summary of core modeling principles for analyzing data.

The volume introduces linear model fundamentals through model vector subspace projections and orthogonal decompositions. It then addresses popular generalized linear models, examining logistic regression for categorical data alongside loglinear models for count responses.

Developed from a graduate course taught at Harvard University, the text includes over 400 exercises to practice theory and data analysis, with companion website datasets available for study.