This book provides conceptual, user-friendly coverage of the generalized linear model (GLM). Themes covered include testing assumptions, examining data quality, and nonlinear and non-additive effects modelled within different types of linear models.

This book explores the fun things researchers can do with logistic regression, explicates and simplifies the confounding complexities of understanding what logistic regression is, and provides evidence-based guidance as to what the best practices in performing logistic regression are.